id	sid	tid	token	lemma	pos
cana-1621	1	1	communications	communication	NOUN
cana-1621	1	2	on	on	ADP
cana-1621	1	3	applied	apply	VERB
cana-1621	1	4	nonlinear	nonlinear	ADJ
cana-1621	1	5	analysis	analysis	NOUN
cana-1621	1	6	issn	issn	NOUN
cana-1621	1	7	:	:	PUNCT
cana-1621	1	8	1074	1074	NUM
cana-1621	1	9	-	-	PUNCT
cana-1621	1	10	133x	133x	NUM
cana-1621	1	11	vol	vol	NOUN
cana-1621	1	12	32	32	NUM
cana-1621	1	13	no	no	NOUN
cana-1621	1	14	.	.	NOUN
cana-1621	1	15	1	1	NUM
cana-1621	1	16	(	(	PUNCT
cana-1621	1	17	2025	2025	NUM
cana-1621	1	18	)	)	PUNCT
cana-1621	1	19	62	62	NUM
cana-1621	1	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1621	1	21	a	a	DET
cana-1621	1	22	hybrid	hybrid	ADJ
cana-1621	1	23	feature	feature	NOUN
cana-1621	1	24	selection	selection	NOUN
cana-1621	1	25	through	through	ADP
cana-1621	1	26	ensemble	ensemble	ADJ
cana-1621	1	27	rank	rank	NOUN
cana-1621	1	28	aggregation	aggregation	NOUN
cana-1621	1	29	to	to	PART
cana-1621	1	30	improve	improve	VERB
cana-1621	1	31	perdition	perdition	NOUN
cana-1621	1	32	and	and	CCONJ
cana-1621	1	33	classification	classification	NOUN
cana-1621	1	34	accuracy	accuracy	NOUN
cana-1621	1	35	jismy	jismy	NOUN
cana-1621	1	36	joseph1	joseph1	NOUN
cana-1621	1	37	,	,	PUNCT
cana-1621	1	38	dr.k.ramesh2	dr.k.ramesh2	PROPN
cana-1621	1	39	phd	phd	PROPN
cana-1621	1	40	research	research	PROPN
cana-1621	1	41	scholar1	scholar1	PROPN
cana-1621	1	42	,	,	PUNCT
cana-1621	1	43	head	head	NOUN
cana-1621	1	44	cum	cum	NOUN
cana-1621	1	45	assistant	assistant	PROPN
cana-1621	1	46	professor2	professor2	PROPN
cana-1621	1	47	department	department	PROPN
cana-1621	1	48	of	of	ADP
cana-1621	1	49	computer	computer	NOUN
cana-1621	1	50	science	science	NOUN
cana-1621	1	51	and	and	CCONJ
cana-1621	1	52	applications	application	NOUN
cana-1621	1	53	,	,	PUNCT
cana-1621	1	54	vivekanandha	vivekanandha	PROPN
cana-1621	1	55	college	college	NOUN
cana-1621	1	56	of	of	ADP
cana-1621	1	57	arts	art	NOUN
cana-1621	1	58	and	and	CCONJ
cana-1621	1	59	science	science	NOUN
cana-1621	1	60	for	for	ADP
cana-1621	1	61	women	woman	NOUN
cana-1621	1	62	(	(	PUNCT
cana-1621	1	63	autonomous	autonomous	ADJ
cana-1621	1	64	)	)	PUNCT
cana-1621	1	65	,	,	PUNCT
cana-1621	1	66	elayampalayam	elayampalayam	ADV
cana-1621	1	67	,	,	PUNCT
cana-1621	1	68	thiruchengode	thiruchengode	PROPN
cana-1621	1	69	,	,	PUNCT
cana-1621	1	70	tamil	tamil	PROPN
cana-1621	1	71	nadu	nadu	PROPN
cana-1621	1	72	,	,	PUNCT
cana-1621	1	73	india	india	PROPN
cana-1621	1	74	email	email	NOUN
cana-1621	1	75	:	:	PUNCT
cana-1621	1	76	jismyjoseph2018@gmail.com1	jismyjoseph2018@gmail.com1	PROPN
cana-1621	1	77	,	,	PUNCT
cana-1621	1	78	drjkkanimozhi@gmail.com2	drjkkanimozhi@gmail.com2	PROPN
cana-1621	1	79	article	article	PROPN
cana-1621	1	80	history	history	NOUN
cana-1621	1	81	:	:	PUNCT
cana-1621	1	82	received	receive	VERB
cana-1621	1	83	:	:	PUNCT
cana-1621	1	84	06	06	NUM
cana-1621	1	85	-	-	SYM
cana-1621	1	86	07	07	NUM
cana-1621	1	87	-	-	PUNCT
cana-1621	1	88	2024	2024	NUM
cana-1621	1	89	revised	revise	VERB
cana-1621	1	90	:	:	PUNCT
cana-1621	1	91	23	23	NUM
cana-1621	1	92	-	-	SYM
cana-1621	1	93	08	08	NUM
cana-1621	1	94	-	-	PUNCT
cana-1621	1	95	2024	2024	NUM
cana-1621	1	96	accepted	accept	VERB
cana-1621	1	97	:	:	PUNCT
cana-1621	1	98	03	03	NUM
cana-1621	1	99	-	-	PUNCT
cana-1621	1	100	09	09	NUM
cana-1621	1	101	-	-	PUNCT
cana-1621	1	102	2024	2024	NUM
cana-1621	1	103	abstract	abstract	NOUN
cana-1621	1	104	:	:	PUNCT
cana-1621	1	105	today	today	NOUN
cana-1621	1	106	,	,	PUNCT
cana-1621	1	107	extending	extend	VERB
cana-1621	1	108	credit	credit	NOUN
cana-1621	1	109	is	be	AUX
cana-1621	1	110	a	a	DET
cana-1621	1	111	difficult	difficult	ADJ
cana-1621	1	112	operation	operation	NOUN
cana-1621	1	113	since	since	SCONJ
cana-1621	1	114	credit	credit	NOUN
cana-1621	1	115	databases	database	NOUN
cana-1621	1	116	contain	contain	VERB
cana-1621	1	117	a	a	DET
cana-1621	1	118	large	large	ADJ
cana-1621	1	119	quantity	quantity	NOUN
cana-1621	1	120	of	of	ADP
cana-1621	1	121	data	datum	NOUN
cana-1621	1	122	as	as	ADV
cana-1621	1	123	well	well	ADV
cana-1621	1	124	as	as	ADP
cana-1621	1	125	redundant	redundant	ADJ
cana-1621	1	126	and	and	CCONJ
cana-1621	1	127	useless	useless	ADJ
cana-1621	1	128	information	information	NOUN
cana-1621	1	129	.	.	PUNCT
cana-1621	2	1	the	the	DET
cana-1621	2	2	surplus	surplus	NOUN
cana-1621	2	3	and	and	CCONJ
cana-1621	2	4	unrelated	unrelated	ADJ
cana-1621	2	5	data	datum	NOUN
cana-1621	2	6	can	can	AUX
cana-1621	2	7	lower	lower	VERB
cana-1621	2	8	the	the	DET
cana-1621	2	9	categorization	categorization	NOUN
cana-1621	2	10	and	and	CCONJ
cana-1621	2	11	prediction	prediction	NOUN
cana-1621	2	12	accuracy	accuracy	NOUN
cana-1621	2	13	.	.	PUNCT
cana-1621	3	1	in	in	ADP
cana-1621	3	2	this	this	DET
cana-1621	3	3	case	case	NOUN
cana-1621	3	4	,	,	PUNCT
cana-1621	3	5	feature	feature	NOUN
cana-1621	3	6	selection	selection	NOUN
cana-1621	3	7	is	be	AUX
cana-1621	3	8	crucial	crucial	ADJ
cana-1621	3	9	for	for	ADP
cana-1621	3	10	managing	manage	VERB
cana-1621	3	11	massive	massive	ADJ
cana-1621	3	12	data	datum	NOUN
cana-1621	3	13	.	.	PUNCT
cana-1621	4	1	different	different	ADJ
cana-1621	4	2	rank	rank	NOUN
cana-1621	4	3	aggregation	aggregation	NOUN
cana-1621	4	4	(	(	PUNCT
cana-1621	4	5	ra	ra	NOUN
cana-1621	4	6	)	)	PUNCT
cana-1621	4	7	methods	method	NOUN
cana-1621	4	8	are	be	AUX
cana-1621	4	9	there	there	ADV
cana-1621	4	10	to	to	PART
cana-1621	4	11	ensemble	ensemble	VERB
cana-1621	4	12	individual	individual	ADJ
cana-1621	4	13	feature	feature	NOUN
cana-1621	4	14	selection	selection	NOUN
cana-1621	4	15	.	.	PUNCT
cana-1621	5	1	however	however	ADV
cana-1621	5	2	not	not	PART
cana-1621	5	3	every	every	DET
cana-1621	5	4	dataset	dataset	NOUN
cana-1621	5	5	will	will	AUX
cana-1621	5	6	perform	perform	VERB
cana-1621	5	7	at	at	ADP
cana-1621	5	8	its	its	PRON
cana-1621	5	9	best	good	ADJ
cana-1621	5	10	when	when	SCONJ
cana-1621	5	11	using	use	VERB
cana-1621	5	12	a	a	DET
cana-1621	5	13	single	single	ADJ
cana-1621	5	14	ra	ra	NOUN
cana-1621	5	15	technique	technique	NOUN
cana-1621	5	16	,	,	PUNCT
cana-1621	5	17	the	the	DET
cana-1621	5	18	combination	combination	NOUN
cana-1621	5	19	of	of	ADP
cana-1621	5	20	multiple	multiple	ADJ
cana-1621	5	21	ra	ra	PROPN
cana-1621	5	22	techniques	technique	NOUN
cana-1621	5	23	are	be	AUX
cana-1621	5	24	needed	need	VERB
cana-1621	5	25	to	to	PART
cana-1621	5	26	increase	increase	VERB
cana-1621	5	27	the	the	DET
cana-1621	5	28	perdition	perdition	NOUN
cana-1621	5	29	accuracy	accuracy	NOUN
cana-1621	5	30	.	.	PUNCT
cana-1621	6	1	this	this	DET
cana-1621	6	2	study	study	NOUN
cana-1621	6	3	proposes	propose	VERB
cana-1621	6	4	a	a	DET
cana-1621	6	5	hybrid	hybrid	ADJ
cana-1621	6	6	rank	rank	NOUN
cana-1621	6	7	aggregation	aggregation	NOUN
cana-1621	6	8	model	model	NOUN
cana-1621	6	9	that	that	PRON
cana-1621	6	10	select	select	ADJ
cana-1621	6	11	features	feature	NOUN
cana-1621	6	12	that	that	PRON
cana-1621	6	13	are	be	AUX
cana-1621	6	14	significant	significant	ADJ
cana-1621	6	15	across	across	ADP
cana-1621	6	16	different	different	ADJ
cana-1621	6	17	rank	rank	NOUN
cana-1621	6	18	aggregation	aggregation	NOUN
cana-1621	6	19	methods	method	NOUN
cana-1621	6	20	like	like	ADP
cana-1621	6	21	mc4	mc4	PROPN
cana-1621	6	22	,	,	PUNCT
cana-1621	6	23	kendall	kendall	PROPN
cana-1621	6	24	tau	tau	PROPN
cana-1621	6	25	distance	distance	NOUN
cana-1621	6	26	and	and	CCONJ
cana-1621	6	27	borda	borda	NOUN
cana-1621	6	28	.	.	PUNCT
cana-1621	7	1	this	this	DET
cana-1621	7	2	study	study	NOUN
cana-1621	7	3	observed	observe	VERB
cana-1621	7	4	that	that	SCONJ
cana-1621	7	5	the	the	DET
cana-1621	7	6	performance	performance	NOUN
cana-1621	7	7	of	of	ADP
cana-1621	7	8	ensemble	ensemble	ADJ
cana-1621	7	9	rank	rank	NOUN
cana-1621	7	10	aggregation	aggregation	NOUN
cana-1621	7	11	techniques	technique	NOUN
cana-1621	7	12	is	be	AUX
cana-1621	7	13	better	well	ADJ
cana-1621	7	14	than	than	ADP
cana-1621	7	15	the	the	DET
cana-1621	7	16	existing	exist	VERB
cana-1621	7	17	individual	individual	ADJ
cana-1621	7	18	rank	rank	NOUN
cana-1621	7	19	aggregation	aggregation	NOUN
cana-1621	7	20	methods	method	NOUN
cana-1621	7	21	.	.	PUNCT
cana-1621	8	1	keywords	keyword	NOUN
cana-1621	8	2	:	:	PUNCT
cana-1621	8	3	ensemble	ensemble	ADJ
cana-1621	8	4	ensemble	ensemble	ADJ
cana-1621	8	5	rank	rank	NOUN
cana-1621	8	6	aggregation	aggregation	NOUN
cana-1621	8	7	,	,	PUNCT
cana-1621	8	8	chi	chi	PROPN
cana-1621	8	9	square	square	PROPN
cana-1621	8	10	.	.	PUNCT
cana-1621	9	1	1	1	X
cana-1621	9	2	.	.	X
cana-1621	9	3	introduction	introduction	NOUN
cana-1621	9	4	last	last	ADJ
cana-1621	9	5	few	few	ADJ
cana-1621	9	6	decades	decade	NOUN
cana-1621	9	7	,	,	PUNCT
cana-1621	9	8	the	the	DET
cana-1621	9	9	size	size	NOUN
cana-1621	9	10	of	of	ADP
cana-1621	9	11	data	datum	NOUN
cana-1621	9	12	is	be	AUX
cana-1621	9	13	exponentially	exponentially	ADV
cana-1621	9	14	increasing	increase	VERB
cana-1621	9	15	day	day	NOUN
cana-1621	9	16	by	by	ADP
cana-1621	9	17	day	day	NOUN
cana-1621	9	18	,	,	PUNCT
cana-1621	9	19	hence	hence	ADV
cana-1621	9	20	more	more	ADV
cana-1621	9	21	efficient	efficient	ADJ
cana-1621	9	22	data	datum	NOUN
cana-1621	9	23	mining	mining	NOUN
cana-1621	9	24	techniques	technique	NOUN
cana-1621	9	25	are	be	AUX
cana-1621	9	26	necessary	necessary	ADJ
cana-1621	9	27	for	for	ADP
cana-1621	9	28	credit	credit	NOUN
cana-1621	9	29	risk	risk	NOUN
cana-1621	9	30	analysis	analysis	NOUN
cana-1621	9	31	.	.	PUNCT
cana-1621	10	1	if	if	SCONJ
cana-1621	10	2	a	a	DET
cana-1621	10	3	model	model	NOUN
cana-1621	10	4	is	be	AUX
cana-1621	10	5	trained	train	VERB
cana-1621	10	6	by	by	ADP
cana-1621	10	7	collecting	collect	VERB
cana-1621	10	8	enormous	enormous	ADJ
cana-1621	10	9	quantities	quantity	NOUN
cana-1621	10	10	of	of	ADP
cana-1621	10	11	data	datum	NOUN
cana-1621	10	12	,	,	PUNCT
cana-1621	10	13	the	the	DET
cana-1621	10	14	model	model	NOUN
cana-1621	10	15	may	may	AUX
cana-1621	10	16	capture	capture	VERB
cana-1621	10	17	insignificant	insignificant	ADJ
cana-1621	10	18	pattern	pattern	NOUN
cana-1621	10	19	it	it	PRON
cana-1621	10	20	the	the	DET
cana-1621	10	21	data	datum	NOUN
cana-1621	10	22	set	set	VERB
cana-1621	10	23	contains	contain	VERB
cana-1621	10	24	of	of	ADP
cana-1621	10	25	noise	noise	NOUN
cana-1621	10	26	,	,	PUNCT
cana-1621	10	27	irrelevant	irrelevant	ADJ
cana-1621	10	28	and	and	CCONJ
cana-1621	10	29	redundant	redundant	ADJ
cana-1621	10	30	features	feature	NOUN
cana-1621	10	31	.	.	PUNCT
cana-1621	11	1	the	the	DET
cana-1621	11	2	recent	recent	ADJ
cana-1621	11	3	development	development	NOUN
cana-1621	11	4	familiarises	familiarise	VERB
cana-1621	11	5	new	new	ADJ
cana-1621	11	6	set	set	NOUN
cana-1621	11	7	of	of	ADP
cana-1621	11	8	data	datum	NOUN
cana-1621	11	9	types	type	NOUN
cana-1621	11	10	and	and	CCONJ
cana-1621	11	11	features	feature	NOUN
cana-1621	11	12	,	,	PUNCT
cana-1621	11	13	hence	hence	ADV
cana-1621	11	14	it	it	PRON
cana-1621	11	15	is	be	AUX
cana-1621	11	16	necessary	necessary	ADJ
cana-1621	11	17	to	to	PART
cana-1621	11	18	build	build	VERB
cana-1621	11	19	a	a	DET
cana-1621	11	20	new	new	ADJ
cana-1621	11	21	scalable	scalable	ADJ
cana-1621	11	22	feature	feature	NOUN
cana-1621	11	23	selection	selection	NOUN
cana-1621	11	24	algorithms	algorithm	NOUN
cana-1621	11	25	for	for	ADP
cana-1621	11	26	creating	create	VERB
cana-1621	11	27	an	an	DET
cana-1621	11	28	accurate	accurate	ADJ
cana-1621	11	29	model	model	NOUN
cana-1621	11	30	for	for	ADP
cana-1621	11	31	credit	credit	NOUN
cana-1621	11	32	risk	risk	NOUN
cana-1621	11	33	analysis	analysis	NOUN
cana-1621	11	34	.	.	PUNCT
cana-1621	12	1	in	in	ADP
cana-1621	12	2	this	this	DET
cana-1621	12	3	situation	situation	NOUN
cana-1621	12	4	,	,	PUNCT
cana-1621	12	5	frequent	frequent	ADJ
cana-1621	12	6	subset	subset	NOUN
cana-1621	12	7	selection	selection	NOUN
cana-1621	12	8	is	be	AUX
cana-1621	12	9	a	a	DET
cana-1621	12	10	crucial	crucial	ADJ
cana-1621	12	11	strategy	strategy	NOUN
cana-1621	12	12	for	for	ADP
cana-1621	12	13	dimensionality	dimensionality	NOUN
cana-1621	12	14	reduction	reduction	NOUN
cana-1621	12	15	and	and	CCONJ
cana-1621	12	16	for	for	ADP
cana-1621	12	17	cutting	cut	VERB
cana-1621	12	18	down	down	ADP
cana-1621	12	19	on	on	ADP
cana-1621	12	20	the	the	DET
cana-1621	12	21	training	training	NOUN
cana-1621	12	22	time	time	NOUN
cana-1621	12	23	for	for	SCONJ
cana-1621	12	24	the	the	DET
cana-1621	12	25	data	datum	NOUN
cana-1621	12	26	set	set	VERB
cana-1621	12	27	.	.	PUNCT
cana-1621	13	1	the	the	DET
cana-1621	13	2	training	training	NOUN
cana-1621	13	3	dataset	dataset	NOUN
cana-1621	13	4	's	's	PART
cana-1621	13	5	features	feature	NOUN
cana-1621	13	6	that	that	PRON
cana-1621	13	7	have	have	VERB
cana-1621	13	8	no	no	DET
cana-1621	13	9	correlation	correlation	NOUN
cana-1621	13	10	to	to	ADP
cana-1621	13	11	the	the	DET
cana-1621	13	12	class	class	NOUN
cana-1621	13	13	labels	label	NOUN
cana-1621	13	14	are	be	AUX
cana-1621	13	15	removed	remove	VERB
cana-1621	13	16	using	use	VERB
cana-1621	13	17	a	a	DET
cana-1621	13	18	feature	feature	NOUN
cana-1621	13	19	selection	selection	NOUN
cana-1621	13	20	,	,	PUNCT
cana-1621	13	21	also	also	ADV
cana-1621	13	22	known	know	VERB
cana-1621	13	23	as	as	ADP
cana-1621	13	24	a	a	DET
cana-1621	13	25	variable	variable	ADJ
cana-1621	13	26	subset	subset	NOUN
cana-1621	13	27	selection	selection	NOUN
cana-1621	14	1	[	[	X
cana-1621	14	2	1	1	NUM
cana-1621	14	3	]	]	PUNCT
cana-1621	14	4	.	.	PUNCT
cana-1621	15	1	it	it	PRON
cana-1621	15	2	is	be	AUX
cana-1621	15	3	a	a	DET
cana-1621	15	4	method	method	NOUN
cana-1621	15	5	for	for	ADP
cana-1621	15	6	selecting	select	VERB
cana-1621	15	7	relevant	relevant	ADJ
cana-1621	15	8	features	feature	NOUN
cana-1621	15	9	and	and	CCONJ
cana-1621	15	10	automatically	automatically	ADV
cana-1621	15	11	removing	remove	VERB
cana-1621	15	12	noise	noise	NOUN
cana-1621	15	13	from	from	ADP
cana-1621	15	14	data	data	PROPN
cana-1621	15	15	.	.	PUNCT
cana-1621	16	1	the	the	DET
cana-1621	16	2	potential	potential	NOUN
cana-1621	16	3	to	to	PART
cana-1621	16	4	avoid	avoid	VERB
cana-1621	16	5	over	over	ADP
cana-1621	16	6	fitting	fitting	ADJ
cana-1621	16	7	,	,	PUNCT
cana-1621	16	8	increase	increase	NOUN
cana-1621	16	9	accuracy	accuracy	NOUN
cana-1621	16	10	,	,	PUNCT
cana-1621	16	11	shorten	shorten	VERB
cana-1621	16	12	training	training	NOUN
cana-1621	16	13	times	time	NOUN
cana-1621	16	14	,	,	PUNCT
cana-1621	16	15	and	and	CCONJ
cana-1621	16	16	simplify	simplify	NOUN
cana-1621	16	17	models	model	NOUN
cana-1621	16	18	are	be	AUX
cana-1621	16	19	all	all	PRON
cana-1621	16	20	advantages	advantage	NOUN
cana-1621	16	21	of	of	ADP
cana-1621	16	22	feature	feature	NOUN
cana-1621	16	23	selection	selection	NOUN
cana-1621	16	24	.	.	PUNCT
cana-1621	17	1	there	there	PRON
cana-1621	17	2	are	be	VERB
cana-1621	17	3	three	three	NUM
cana-1621	17	4	methods	method	NOUN
cana-1621	17	5	for	for	ADP
cana-1621	17	6	selecting	select	VERB
cana-1621	17	7	features	feature	NOUN
cana-1621	17	8	filter	filter	NOUN
cana-1621	17	9	,	,	PUNCT
cana-1621	17	10	wrapper	wrapper	NOUN
cana-1621	17	11	,	,	PUNCT
cana-1621	17	12	and	and	CCONJ
cana-1621	17	13	hybrid	hybrid	NOUN
cana-1621	17	14	.	.	PUNCT
cana-1621	18	1	in	in	ADP
cana-1621	18	2	order	order	NOUN
cana-1621	18	3	to	to	PART
cana-1621	18	4	integrate	integrate	VERB
cana-1621	18	5	the	the	DET
cana-1621	18	6	results	result	NOUN
cana-1621	18	7	of	of	ADP
cana-1621	18	8	several	several	ADJ
cana-1621	18	9	feature	feature	NOUN
cana-1621	18	10	selection	selection	NOUN
cana-1621	18	11	approaches	approach	NOUN
cana-1621	18	12	like	like	ADP
cana-1621	18	13	chi	chi	NOUN
cana-1621	18	14	-	-	PUNCT
cana-1621	18	15	square	square	ADJ
cana-1621	18	16	,	,	PUNCT
cana-1621	18	17	information	information	NOUN
cana-1621	18	18	gain	gain	NOUN
cana-1621	18	19	,	,	PUNCT
cana-1621	18	20	fisher	fisher	PROPN
cana-1621	18	21	score	score	NOUN
cana-1621	18	22	,	,	PUNCT
cana-1621	18	23	etc	etc	X
cana-1621	18	24	.	.	X
cana-1621	18	25	,	,	PUNCT
cana-1621	18	26	it	it	PRON
cana-1621	18	27	is	be	AUX
cana-1621	18	28	necessary	necessary	ADJ
cana-1621	18	29	to	to	PART
cana-1621	18	30	use	use	VERB
cana-1621	18	31	the	the	DET
cana-1621	18	32	rank	rank	NOUN
cana-1621	18	33	aggregation	aggregation	NOUN
cana-1621	18	34	(	(	PUNCT
cana-1621	18	35	ra	ra	NOUN
cana-1621	18	36	)	)	PUNCT
cana-1621	18	37	methodology	methodology	NOUN
cana-1621	18	38	,	,	PUNCT
cana-1621	18	39	which	which	PRON
cana-1621	18	40	combines	combine	VERB
cana-1621	18	41	many	many	ADJ
cana-1621	18	42	ranked	rank	VERB
cana-1621	18	43	lists	list	NOUN
cana-1621	18	44	into	into	ADP
cana-1621	18	45	a	a	DET
cana-1621	18	46	single	single	ADJ
cana-1621	18	47	ranking	ranking	NOUN
cana-1621	18	48	.	.	PUNCT
cana-1621	19	1	in	in	ADP
cana-1621	19	2	this	this	DET
cana-1621	19	3	paper	paper	NOUN
cana-1621	19	4	we	we	PRON
cana-1621	19	5	propose	propose	VERB
cana-1621	19	6	a	a	DET
cana-1621	19	7	hybrid	hybrid	ADJ
cana-1621	19	8	feature	feature	NOUN
cana-1621	19	9	selection	selection	NOUN
cana-1621	19	10	through	through	ADP
cana-1621	19	11	ensemble	ensemble	ADJ
cana-1621	19	12	rank	rank	NOUN
cana-1621	19	13	aggregation	aggregation	NOUN
cana-1621	19	14	(	(	PUNCT
cana-1621	19	15	hfsera	hfsera	NOUN
cana-1621	19	16	)	)	PUNCT
cana-1621	19	17	to	to	PART
cana-1621	19	18	improve	improve	VERB
cana-1621	19	19	perdition	perdition	NOUN
cana-1621	19	20	and	and	CCONJ
cana-1621	19	21	classification	classification	NOUN
cana-1621	19	22	accuracy	accuracy	NOUN
cana-1621	19	23	.	.	PUNCT
cana-1621	20	1	communications	communication	NOUN
cana-1621	20	2	on	on	ADP
cana-1621	20	3	applied	apply	VERB
cana-1621	20	4	nonlinear	nonlinear	ADJ
cana-1621	20	5	analysis	analysis	NOUN
cana-1621	20	6	issn	issn	NOUN
cana-1621	20	7	:	:	PUNCT
cana-1621	20	8	1074	1074	NUM
cana-1621	20	9	-	-	PUNCT
cana-1621	20	10	133x	133x	NUM
cana-1621	20	11	vol	vol	NOUN
cana-1621	20	12	32	32	NUM
cana-1621	20	13	no	no	NOUN
cana-1621	20	14	.	.	NOUN
cana-1621	20	15	1	1	NUM
cana-1621	20	16	(	(	PUNCT
cana-1621	20	17	2025	2025	NUM
cana-1621	20	18	)	)	PUNCT
cana-1621	20	19	63	63	NUM
cana-1621	20	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1621	20	21	2	2	X
cana-1621	20	22	.	.	X
cana-1621	20	23	literature	literature	NOUN
cana-1621	20	24	review	review	NOUN
cana-1621	20	25	it	it	PRON
cana-1621	20	26	has	have	AUX
cana-1621	20	27	been	be	AUX
cana-1621	20	28	demonstrated	demonstrate	VERB
cana-1621	20	29	that	that	SCONJ
cana-1621	20	30	hybrid	hybrid	ADJ
cana-1621	20	31	feature	feature	NOUN
cana-1621	20	32	selection	selection	NOUN
cana-1621	20	33	methods	method	NOUN
cana-1621	20	34	increase	increase	VERB
cana-1621	20	35	classification	classification	NOUN
cana-1621	20	36	accuracy	accuracy	NOUN
cana-1621	20	37	.	.	PUNCT
cana-1621	21	1	recent	recent	ADJ
cana-1621	21	2	works	work	NOUN
cana-1621	21	3	that	that	PRON
cana-1621	21	4	suggest	suggest	VERB
cana-1621	21	5	hybrid	hybrid	ADJ
cana-1621	21	6	feature	feature	NOUN
cana-1621	21	7	selection	selection	NOUN
cana-1621	21	8	methods	method	NOUN
cana-1621	21	9	are	be	AUX
cana-1621	21	10	scarce	scarce	ADJ
cana-1621	21	11	.	.	PUNCT
cana-1621	22	1	a	a	DET
cana-1621	22	2	few	few	ADJ
cana-1621	22	3	hybrid	hybrid	ADJ
cana-1621	22	4	feature	feature	NOUN
cana-1621	22	5	selection	selection	NOUN
cana-1621	22	6	strategies	strategy	NOUN
cana-1621	22	7	are	be	AUX
cana-1621	22	8	been	be	AUX
cana-1621	22	9	put	put	VERB
cana-1621	22	10	out	out	ADP
cana-1621	22	11	specifically	specifically	ADV
cana-1621	22	12	for	for	ADP
cana-1621	22	13	credit	credit	NOUN
cana-1621	22	14	datasets	dataset	NOUN
cana-1621	22	15	.	.	PUNCT
cana-1621	23	1	in	in	ADP
cana-1621	23	2	the	the	DET
cana-1621	23	3	paper	paper	NOUN
cana-1621	23	4	‘	'	PUNCT
cana-1621	23	5	a	a	DET
cana-1621	23	6	hybrid	hybrid	ADJ
cana-1621	23	7	feature	feature	NOUN
cana-1621	23	8	selection	selection	NOUN
cana-1621	23	9	model	model	NOUN
cana-1621	23	10	based	base	VERB
cana-1621	23	11	on	on	ADP
cana-1621	23	12	improved	improved	ADJ
cana-1621	23	13	squirrel	squirrel	NOUN
cana-1621	23	14	search	search	NOUN
cana-1621	23	15	algorithm	algorithm	NOUN
cana-1621	23	16	and	and	CCONJ
cana-1621	23	17	rank	rank	NOUN
cana-1621	23	18	aggregation	aggregation	NOUN
cana-1621	23	19	using	use	VERB
cana-1621	23	20	fuzzy	fuzzy	ADJ
cana-1621	23	21	techniques	technique	NOUN
cana-1621	23	22	for	for	ADP
cana-1621	23	23	biomedical	biomedical	ADJ
cana-1621	23	24	data	datum	NOUN
cana-1621	23	25	classification	classification	NOUN
cana-1621	23	26	’	'	PUNCT
cana-1621	24	1	[	[	X
cana-1621	24	2	3	3	X
cana-1621	24	3	]	]	X
cana-1621	24	4	gayathri	gayathri	PROPN
cana-1621	24	5	nagarajan	nagarajan	PROPN
cana-1621	24	6	and	and	CCONJ
cana-1621	24	7	l.	l.	PROPN
cana-1621	24	8	d.	d.	PROPN
cana-1621	24	9	dhinesh	dhinesh	PROPN
cana-1621	24	10	babu	babu	PROPN
cana-1621	24	11	proposed	propose	VERB
cana-1621	24	12	a	a	DET
cana-1621	24	13	hybrid	hybrid	ADJ
cana-1621	24	14	model	model	NOUN
cana-1621	24	15	for	for	ADP
cana-1621	24	16	feature	feature	NOUN
cana-1621	24	17	selection	selection	NOUN
cana-1621	24	18	in	in	ADP
cana-1621	24	19	biomedical	biomedical	ADJ
cana-1621	24	20	data	datum	NOUN
cana-1621	24	21	classification	classification	NOUN
cana-1621	24	22	and	and	CCONJ
cana-1621	24	23	their	their	PRON
cana-1621	24	24	model	model	NOUN
cana-1621	24	25	is	be	AUX
cana-1621	24	26	compared	compare	VERB
cana-1621	24	27	with	with	ADP
cana-1621	24	28	other	other	ADJ
cana-1621	24	29	existing	exist	VERB
cana-1621	24	30	models	model	NOUN
cana-1621	24	31	.	.	PUNCT
cana-1621	25	1	they	they	PRON
cana-1621	25	2	claimed	claim	VERB
cana-1621	25	3	that	that	SCONJ
cana-1621	25	4	their	their	PRON
cana-1621	25	5	model	model	NOUN
cana-1621	25	6	performed	perform	VERB
cana-1621	25	7	better	well	ADV
cana-1621	25	8	than	than	ADP
cana-1621	25	9	other	other	ADJ
cana-1621	25	10	individual	individual	ADJ
cana-1621	25	11	filtering	filter	VERB
cana-1621	25	12	methods	method	NOUN
cana-1621	25	13	in	in	ADP
cana-1621	25	14	terms	term	NOUN
cana-1621	25	15	of	of	ADP
cana-1621	25	16	classification	classification	NOUN
cana-1621	25	17	accuracy	accuracy	NOUN
cana-1621	25	18	and	and	CCONJ
cana-1621	25	19	time	time	NOUN
cana-1621	25	20	needed	need	VERB
cana-1621	25	21	for	for	ADP
cana-1621	25	22	classification	classification	NOUN
cana-1621	25	23	.	.	PUNCT
cana-1621	26	1	in	in	ADP
cana-1621	26	2	[	[	X
cana-1621	26	3	4	4	NUM
cana-1621	26	4	]	]	X
cana-1621	26	5	rahi	rahi	NOUN
cana-1621	26	6	jain	jain	PROPN
cana-1621	26	7	,	,	PUNCT
cana-1621	26	8	wei	wei	PROPN
cana-1621	26	9	xu	xu	PROPN
cana-1621	26	10	,	,	PUNCT
cana-1621	26	11	presents	present	VERB
cana-1621	26	12	a	a	DET
cana-1621	26	13	novel	novel	ADJ
cana-1621	26	14	hybrid	hybrid	ADJ
cana-1621	26	15	rank	rank	NOUN
cana-1621	26	16	aggregation	aggregation	NOUN
cana-1621	26	17	(	(	PUNCT
cana-1621	26	18	hra	hra	PROPN
cana-1621	26	19	)	)	PUNCT
cana-1621	26	20	strategy	strategy	NOUN
cana-1621	26	21	to	to	PART
cana-1621	26	22	carry	carry	VERB
cana-1621	26	23	out	out	ADP
cana-1621	26	24	the	the	DET
cana-1621	26	25	rank	rank	NOUN
cana-1621	26	26	aggregation	aggregation	NOUN
cana-1621	26	27	phase	phase	NOUN
cana-1621	26	28	in	in	ADP
cana-1621	26	29	ensemble	ensemble	ADJ
cana-1621	26	30	feature	feature	NOUN
cana-1621	26	31	selection	selection	NOUN
cana-1621	26	32	that	that	PRON
cana-1621	26	33	permits	permit	VERB
cana-1621	26	34	feature	feature	NOUN
cana-1621	26	35	selection	selection	NOUN
cana-1621	26	36	based	base	VERB
cana-1621	26	37	on	on	ADP
cana-1621	26	38	relevance	relevance	NOUN
cana-1621	26	39	across	across	ADP
cana-1621	26	40	several	several	ADJ
cana-1621	26	41	rank	rank	NOUN
cana-1621	26	42	aggregation	aggregation	NOUN
cana-1621	26	43	methodologies	methodology	NOUN
cana-1621	26	44	.	.	PUNCT
cana-1621	27	1	in	in	ADP
cana-1621	27	2	this	this	DET
cana-1621	27	3	model	model	NOUN
cana-1621	27	4	,	,	PUNCT
cana-1621	27	5	to	to	PART
cana-1621	27	6	choose	choose	VERB
cana-1621	27	7	features	feature	NOUN
cana-1621	27	8	using	use	VERB
cana-1621	27	9	weighted	weight	VERB
cana-1621	27	10	unsupervised	unsupervised	ADJ
cana-1621	27	11	clustering	clustering	NOUN
cana-1621	27	12	,	,	PUNCT
cana-1621	27	13	the	the	DET
cana-1621	27	14	hra	hra	PROPN
cana-1621	27	15	approach	approach	NOUN
cana-1621	27	16	pools	pool	VERB
cana-1621	27	17	the	the	DET
cana-1621	27	18	feature	feature	NOUN
cana-1621	27	19	importance	importance	NOUN
cana-1621	27	20	from	from	ADP
cana-1621	27	21	the	the	DET
cana-1621	27	22	current	current	ADJ
cana-1621	27	23	rank	rank	NOUN
cana-1621	27	24	aggregation	aggregation	NOUN
cana-1621	27	25	approaches	approach	NOUN
cana-1621	27	26	.	.	PUNCT
cana-1621	28	1	this	this	DET
cana-1621	28	2	method	method	NOUN
cana-1621	28	3	is	be	AUX
cana-1621	28	4	adaptable	adaptable	ADJ
cana-1621	28	5	since	since	SCONJ
cana-1621	28	6	a	a	DET
cana-1621	28	7	wide	wide	ADJ
cana-1621	28	8	range	range	NOUN
cana-1621	28	9	of	of	ADP
cana-1621	28	10	ensemble	ensemble	ADJ
cana-1621	28	11	techniques	technique	NOUN
cana-1621	28	12	,	,	PUNCT
cana-1621	28	13	data	datum	NOUN
cana-1621	28	14	types	type	NOUN
cana-1621	28	15	,	,	PUNCT
cana-1621	28	16	and	and	CCONJ
cana-1621	28	17	ra	ra	PROPN
cana-1621	28	18	methods	method	NOUN
cana-1621	28	19	could	could	AUX
cana-1621	28	20	be	be	AUX
cana-1621	28	21	used	use	VERB
cana-1621	28	22	with	with	ADP
cana-1621	28	23	it	it	PRON
cana-1621	28	24	.	.	PUNCT
cana-1621	29	1	in	in	ADP
cana-1621	29	2	[	[	X
cana-1621	29	3	5	5	NUM
cana-1621	29	4	]	]	X
cana-1621	29	5	dahiya	dahiya	PROPN
cana-1621	29	6	,	,	PUNCT
cana-1621	29	7	shashi	shashi	PROPN
cana-1621	29	8	,	,	PUNCT
cana-1621	29	9	handa	handa	PROPN
cana-1621	29	10	,	,	PUNCT
cana-1621	29	11	s.s	s.s	PROPN
cana-1621	29	12	and	and	CCONJ
cana-1621	29	13	singh	singh	PROPN
cana-1621	29	14	,	,	PUNCT
cana-1621	29	15	netra	netra	VERB
cana-1621	29	16	combines	combine	VERB
cana-1621	29	17	different	different	ADJ
cana-1621	29	18	feature	feature	NOUN
cana-1621	29	19	rating	rating	NOUN
cana-1621	29	20	algorithms	algorithm	NOUN
cana-1621	29	21	for	for	ADP
cana-1621	29	22	selecting	select	VERB
cana-1621	29	23	features	feature	NOUN
cana-1621	29	24	from	from	ADP
cana-1621	29	25	credit	credit	NOUN
cana-1621	29	26	data	datum	NOUN
cana-1621	29	27	.	.	PUNCT
cana-1621	30	1	they	they	PRON
cana-1621	30	2	used	use	VERB
cana-1621	30	3	five	five	NUM
cana-1621	30	4	individual	individual	ADJ
cana-1621	30	5	rank	rank	NOUN
cana-1621	30	6	based	base	VERB
cana-1621	30	7	feature	feature	NOUN
cana-1621	30	8	selection	selection	NOUN
cana-1621	30	9	methods	method	NOUN
cana-1621	30	10	and	and	CCONJ
cana-1621	30	11	a	a	DET
cana-1621	30	12	rank	rank	NOUN
cana-1621	30	13	aggregation	aggregation	NOUN
cana-1621	30	14	algorithm	algorithm	NOUN
cana-1621	30	15	for	for	ADP
cana-1621	30	16	combining	combine	VERB
cana-1621	30	17	rank	rank	NOUN
cana-1621	30	18	obtained	obtain	VERB
cana-1621	30	19	from	from	ADP
cana-1621	30	20	these	these	DET
cana-1621	30	21	individual	individual	ADJ
cana-1621	30	22	feature	feature	NOUN
cana-1621	30	23	selection	selection	NOUN
cana-1621	30	24	method	method	NOUN
cana-1621	30	25	.	.	PUNCT
cana-1621	31	1	this	this	DET
cana-1621	31	2	new	new	ADJ
cana-1621	31	3	rank	rank	NOUN
cana-1621	31	4	aggregation	aggregation	NOUN
cana-1621	31	5	algorithm	algorithm	NOUN
cana-1621	31	6	uses	use	VERB
cana-1621	31	7	rank	rank	NOUN
cana-1621	31	8	order	order	NOUN
cana-1621	31	9	and	and	CCONJ
cana-1621	31	10	rank	rank	NOUN
cana-1621	31	11	score	score	NOUN
cana-1621	31	12	of	of	ADP
cana-1621	31	13	the	the	DET
cana-1621	31	14	features	feature	NOUN
cana-1621	31	15	.	.	PUNCT
cana-1621	32	1	they	they	PRON
cana-1621	32	2	proved	prove	VERB
cana-1621	32	3	that	that	SCONJ
cana-1621	32	4	the	the	DET
cana-1621	32	5	performance	performance	NOUN
cana-1621	32	6	of	of	ADP
cana-1621	32	7	this	this	DET
cana-1621	32	8	new	new	ADJ
cana-1621	32	9	rank	rank	NOUN
cana-1621	32	10	aggregation	aggregation	NOUN
cana-1621	32	11	algorithm	algorithm	NOUN
cana-1621	32	12	is	be	AUX
cana-1621	32	13	better	well	ADJ
cana-1621	32	14	than	than	ADP
cana-1621	32	15	other	other	ADJ
cana-1621	32	16	individual	individual	ADJ
cana-1621	32	17	method	method	NOUN
cana-1621	32	18	.	.	PUNCT
cana-1621	33	1	in	in	ADP
cana-1621	33	2	[	[	X
cana-1621	33	3	6	6	NUM
cana-1621	33	4	]	]	X
cana-1621	33	5	wanwan	wanwan	PROPN
cana-1621	33	6	zheng	zheng	PROPN
cana-1621	33	7	;	;	PUNCT
cana-1621	33	8	mingzhe	mingzhe	ADJ
cana-1621	33	9	jin	jin	NOUN
cana-1621	33	10	compared	compare	VERB
cana-1621	33	11	feature	feature	NOUN
cana-1621	33	12	selection	selection	NOUN
cana-1621	33	13	methods	method	NOUN
cana-1621	33	14	by	by	ADP
cana-1621	33	15	using	use	VERB
cana-1621	33	16	rank	rank	NOUN
cana-1621	33	17	aggregation	aggregation	NOUN
cana-1621	33	18	.	.	PUNCT
cana-1621	34	1	in	in	ADP
cana-1621	34	2	this	this	DET
cana-1621	34	3	study	study	NOUN
cana-1621	34	4	they	they	PRON
cana-1621	34	5	used	use	VERB
cana-1621	34	6	10	10	NUM
cana-1621	34	7	different	different	ADJ
cana-1621	34	8	feature	feature	NOUN
cana-1621	34	9	selection	selection	NOUN
cana-1621	34	10	techniques	technique	NOUN
cana-1621	34	11	and	and	CCONJ
cana-1621	34	12	schulze	schulze	NOUN
cana-1621	34	13	(	(	PUNCT
cana-1621	34	14	ssd	ssd	PROPN
cana-1621	34	15	)	)	PUNCT
cana-1621	34	16	rank	rank	NOUN
cana-1621	34	17	aggregation	aggregation	NOUN
cana-1621	34	18	is	be	AUX
cana-1621	34	19	used	use	VERB
cana-1621	34	20	to	to	PART
cana-1621	34	21	combine	combine	VERB
cana-1621	34	22	ranks	rank	NOUN
cana-1621	34	23	together	together	ADV
cana-1621	34	24	.	.	PUNCT
cana-1621	35	1	according	accord	VERB
cana-1621	35	2	to	to	ADP
cana-1621	35	3	their	their	PRON
cana-1621	35	4	analysis	analysis	NOUN
cana-1621	35	5	mahalanobis	mahalanobis	ADJ
cana-1621	35	6	distance	distance	NOUN
cana-1621	35	7	is	be	AUX
cana-1621	35	8	the	the	DET
cana-1621	35	9	most	most	ADV
cana-1621	35	10	effective	effective	ADJ
cana-1621	35	11	approach	approach	NOUN
cana-1621	35	12	overall	overall	ADJ
cana-1621	35	13	.	.	PUNCT
cana-1621	36	1	in	in	ADP
cana-1621	36	2	the	the	DET
cana-1621	36	3	paper	paper	NOUN
cana-1621	36	4	‘	'	PUNCT
cana-1621	36	5	a	a	DET
cana-1621	36	6	rank	rank	NOUN
cana-1621	36	7	aggregation	aggregation	NOUN
cana-1621	36	8	algorithm	algorithm	NOUN
cana-1621	36	9	for	for	ADP
cana-1621	36	10	ensemble	ensemble	ADJ
cana-1621	36	11	of	of	ADP
cana-1621	36	12	multiple	multiple	ADJ
cana-1621	36	13	feature	feature	NOUN
cana-1621	36	14	selection	selection	NOUN
cana-1621	36	15	techniques	technique	NOUN
cana-1621	36	16	in	in	ADP
cana-1621	36	17	credit	credit	NOUN
cana-1621	36	18	risk	risk	NOUN
cana-1621	36	19	evaluation	evaluation	NOUN
cana-1621	36	20	’	'	PUNCT
cana-1621	37	1	[	[	X
cana-1621	37	2	7	7	NUM
cana-1621	37	3	]	]	X
cana-1621	37	4	shashi	shashi	PROPN
cana-1621	37	5	dahiya	dahiya	PROPN
cana-1621	37	6	,	,	PUNCT
cana-1621	37	7	s.s	s.s	PROPN
cana-1621	37	8	handa	handa	PROPN
cana-1621	37	9	and	and	CCONJ
cana-1621	37	10	n.p	n.p	PROPN
cana-1621	37	11	singh	singh	PROPN
cana-1621	37	12	suggested	suggest	VERB
cana-1621	37	13	a	a	DET
cana-1621	37	14	rank	rank	NOUN
cana-1621	37	15	aggregation	aggregation	NOUN
cana-1621	37	16	algorithm	algorithm	NOUN
cana-1621	37	17	for	for	ADP
cana-1621	37	18	combining	combine	VERB
cana-1621	37	19	different	different	ADJ
cana-1621	37	20	feature	feature	NOUN
cana-1621	37	21	selection	selection	NOUN
cana-1621	37	22	techniques	technique	NOUN
cana-1621	37	23	.	.	PUNCT
cana-1621	38	1	they	they	PRON
cana-1621	38	2	used	use	VERB
cana-1621	38	3	chi	chi	PROPN
cana-1621	38	4	-	-	PUNCT
cana-1621	38	5	square	square	ADJ
cana-1621	38	6	,	,	PUNCT
cana-1621	38	7	information	information	NOUN
cana-1621	38	8	gain	gain	NOUN
cana-1621	38	9	,	,	PUNCT
cana-1621	38	10	gain	gain	VERB
cana-1621	38	11	ratio	ratio	NOUN
cana-1621	38	12	,	,	PUNCT
cana-1621	38	13	relief	relief	NOUN
cana-1621	38	14	-	-	PUNCT
cana-1621	38	15	f	f	NOUN
cana-1621	38	16	etc	etc	X
cana-1621	38	17	.	.	X
cana-1621	38	18	for	for	ADP
cana-1621	38	19	feature	feature	NOUN
cana-1621	38	20	selection	selection	NOUN
cana-1621	38	21	.	.	PUNCT
cana-1621	39	1	in	in	ADP
cana-1621	39	2	[	[	X
cana-1621	39	3	8	8	NUM
cana-1621	39	4	]	]	PUNCT
cana-1621	39	5	the	the	DET
cana-1621	39	6	paper	paper	NOUN
cana-1621	39	7	entitled	entitle	VERB
cana-1621	39	8	‘	'	PUNCT
cana-1621	39	9	the	the	DET
cana-1621	39	10	stability	stability	NOUN
cana-1621	39	11	of	of	ADP
cana-1621	39	12	different	different	ADJ
cana-1621	39	13	aggregation	aggregation	NOUN
cana-1621	39	14	techniques	technique	NOUN
cana-1621	39	15	in	in	ADP
cana-1621	39	16	ensemble	ensemble	ADJ
cana-1621	39	17	feature	feature	NOUN
cana-1621	39	18	selection	selection	NOUN
cana-1621	39	19	’	'	PUNCT
cana-1621	39	20	reem	reem	PROPN
cana-1621	39	21	salman	salman	PROPN
cana-1621	39	22	,	,	PUNCT
cana-1621	39	23	ayman	ayman	PROPN
cana-1621	39	24	alzaatreh	alzaatreh	PROPN
cana-1621	39	25	and	and	CCONJ
cana-1621	39	26	hana	hana	PROPN
cana-1621	39	27	sulieman	sulieman	PROPN
cana-1621	39	28	mentioned	mention	VERB
cana-1621	39	29	the	the	DET
cana-1621	39	30	significant	significant	ADJ
cana-1621	39	31	differences	difference	NOUN
cana-1621	39	32	between	between	ADP
cana-1621	39	33	the	the	DET
cana-1621	39	34	score	score	NOUN
cana-1621	39	35	-	-	PUNCT
cana-1621	39	36	based	base	VERB
cana-1621	39	37	and	and	CCONJ
cana-1621	39	38	rank	rank	NOUN
cana-1621	39	39	-	-	PUNCT
cana-1621	39	40	based	base	VERB
cana-1621	39	41	aggregation	aggregation	NOUN
cana-1621	39	42	procedures	procedure	NOUN
cana-1621	39	43	in	in	ADP
cana-1621	39	44	the	the	DET
cana-1621	39	45	ensemble	ensemble	NOUN
cana-1621	39	46	's	's	PART
cana-1621	39	47	stability	stability	NOUN
cana-1621	39	48	and	and	CCONJ
cana-1621	39	49	accuracy	accuracy	NOUN
cana-1621	39	50	behaviour	behaviour	NOUN
cana-1621	39	51	under	under	ADP
cana-1621	39	52	various	various	ADJ
cana-1621	39	53	aggregations	aggregation	NOUN
cana-1621	39	54	.	.	PUNCT
cana-1621	40	1	in	in	ADP
cana-1621	40	2	addition	addition	NOUN
cana-1621	40	3	,	,	PUNCT
cana-1621	40	4	it	it	PRON
cana-1621	40	5	was	be	AUX
cana-1621	40	6	shown	show	VERB
cana-1621	40	7	that	that	SCONJ
cana-1621	40	8	the	the	DET
cana-1621	40	9	simpler	simple	ADJ
cana-1621	40	10	score	score	NOUN
cana-1621	40	11	-	-	PUNCT
cana-1621	40	12	based	base	VERB
cana-1621	40	13	techniques	technique	NOUN
cana-1621	40	14	based	base	VERB
cana-1621	40	15	on	on	ADP
cana-1621	40	16	the	the	DET
cana-1621	40	17	l2	l2	NOUN
cana-1621	40	18	-	-	PUNCT
cana-1621	40	19	norm	norm	NOUN
cana-1621	40	20	or	or	CCONJ
cana-1621	40	21	arithmetic	arithmetic	ADJ
cana-1621	40	22	mean	mean	NOUN
cana-1621	40	23	aggregation	aggregation	NOUN
cana-1621	40	24	seem	seem	VERB
cana-1621	40	25	to	to	PART
cana-1621	40	26	be	be	AUX
cana-1621	40	27	effective	effective	ADJ
cana-1621	40	28	and	and	CCONJ
cana-1621	40	29	convincing	convincing	ADJ
cana-1621	40	30	in	in	ADP
cana-1621	40	31	most	most	ADJ
cana-1621	40	32	situations	situation	NOUN
cana-1621	40	33	.	.	PUNCT
cana-1621	41	1	in	in	ADP
cana-1621	41	2	the	the	DET
cana-1621	41	3	paper[9	paper[9	NOUN
cana-1621	41	4	]	]	PUNCT
cana-1621	41	5	’	'	PUNCT
cana-1621	41	6	frequent	frequent	ADJ
cana-1621	41	7	itemsets	itemset	NOUN
cana-1621	41	8	mining	mining	NOUN
cana-1621	41	9	for	for	ADP
cana-1621	41	10	big	big	ADJ
cana-1621	41	11	data	datum	NOUN
cana-1621	41	12	:	:	PUNCT
cana-1621	41	13	a	a	DET
cana-1621	41	14	comparative	comparative	ADJ
cana-1621	41	15	analysis	analysis	NOUN
cana-1621	41	16	’	'	PUNCT
cana-1621	41	17	daniele	daniele	PROPN
cana-1621	41	18	apiletti	apiletti	PROPN
cana-1621	41	19	,	,	PUNCT
cana-1621	41	20	elena	elena	PROPN
cana-1621	41	21	baralis	baralis	PROPN
cana-1621	41	22	,	,	PUNCT
cana-1621	41	23	tania	tania	PROPN
cana-1621	41	24	cerquite	cerquite	PROPN
cana-1621	41	25	lli	lli	PROPN
cana-1621	41	26	,	,	PUNCT
cana-1621	41	27	paolo	paolo	PROPN
cana-1621	41	28	garza	garza	PROPN
cana-1621	41	29	,	,	PUNCT
cana-1621	41	30	fabio	fabio	PROPN
cana-1621	41	31	pulvirenti	pulvirenti	PROPN
cana-1621	41	32	and	and	CCONJ
cana-1621	41	33	conducted	conduct	VERB
cana-1621	41	34	a	a	DET
cana-1621	41	35	theoretical	theoretical	ADJ
cana-1621	41	36	and	and	CCONJ
cana-1621	41	37	experimental	experimental	ADJ
cana-1621	41	38	comparative	comparative	ADJ
cana-1621	41	39	analyses	analysis	NOUN
cana-1621	41	40	of	of	ADP
cana-1621	41	41	hadoopand	hadoopand	NOUN
cana-1621	41	42	spark	spark	NOUN
cana-1621	41	43	scalable	scalable	ADJ
cana-1621	41	44	algorithms	algorithm	NOUN
cana-1621	41	45	to	to	PART
cana-1621	41	46	find	find	VERB
cana-1621	41	47	frequent	frequent	ADJ
cana-1621	41	48	pattern	pattern	NOUN
cana-1621	41	49	from	from	ADP
cana-1621	41	50	data	data	PROPN
cana-1621	41	51	.	.	PUNCT
cana-1621	42	1	https://ieeexplore.ieee.org/author/37086592767	https://ieeexplore.ieee.org/author/37086592767	PROPN
cana-1621	42	2	https://ieeexplore.ieee.org/author/37086310911	https://ieeexplore.ieee.org/author/37086310911	PROPN
cana-1621	42	3	https://thesai.org/downloads/ijarai/volume5no9/paper_1-a_rank_aggregation_algorithm_for_ensemble.pdf	https://thesai.org/downloads/ijarai/volume5no9/paper_1-a_rank_aggregation_algorithm_for_ensemble.pdf	PROPN
cana-1621	42	4	https://thesai.org/downloads/ijarai/volume5no9/paper_1-a_rank_aggregation_algorithm_for_ensemble.pdf	https://thesai.org/downloads/ijarai/volume5no9/paper_1-a_rank_aggregation_algorithm_for_ensemble.pdf	VERB
cana-1621	42	5	https://journalofbigdata.springeropen.com/articles/10.1186/s40537-022-00607-1#auth-reem-salman	https://journalofbigdata.springeropen.com/articles/10.1186/s40537-022-00607-1#auth-reem-salman	SYM
cana-1621	42	6	https://journalofbigdata.springeropen.com/articles/10.1186/s40537-022-00607-1#auth-ayman-alzaatreh	https://journalofbigdata.springeropen.com/articles/10.1186/s40537-022-00607-1#auth-ayman-alzaatreh	NUM
cana-1621	42	7	https://journalofbigdata.springeropen.com/articles/10.1186/s40537-022-00607-1#auth-hana-sulieman	https://journalofbigdata.springeropen.com/articles/10.1186/s40537-022-00607-1#auth-hana-sulieman	PROPN
cana-1621	42	8	communications	communication	NOUN
cana-1621	42	9	on	on	ADP
cana-1621	42	10	applied	apply	VERB
cana-1621	42	11	nonlinear	nonlinear	ADJ
cana-1621	42	12	analysis	analysis	NOUN
cana-1621	42	13	issn	issn	NOUN
cana-1621	42	14	:	:	PUNCT
cana-1621	42	15	1074	1074	NUM
cana-1621	42	16	-	-	PUNCT
cana-1621	42	17	133x	133x	NUM
cana-1621	42	18	vol	vol	NOUN
cana-1621	42	19	32	32	NUM
cana-1621	42	20	no	no	NOUN
cana-1621	42	21	.	.	NOUN
cana-1621	42	22	1	1	NUM
cana-1621	42	23	(	(	PUNCT
cana-1621	42	24	2025	2025	NUM
cana-1621	42	25	)	)	PUNCT
cana-1621	42	26	64	64	NUM
cana-1621	42	27	https://internationalpubls.com	https://internationalpubls.com	X
cana-1621	42	28	3	3	X
cana-1621	42	29	.	.	PUNCT
cana-1621	42	30	hybrid	hybrid	ADJ
cana-1621	42	31	feature	feature	NOUN
cana-1621	42	32	selection	selection	NOUN
cana-1621	42	33	using	use	VERB
cana-1621	42	34	ensemble	ensemble	ADJ
cana-1621	42	35	rank	rank	NOUN
cana-1621	42	36	aggregation	aggregation	NOUN
cana-1621	42	37	this	this	DET
cana-1621	42	38	section	section	NOUN
cana-1621	42	39	includes	include	VERB
cana-1621	42	40	the	the	DET
cana-1621	42	41	information	information	NOUN
cana-1621	42	42	about	about	ADP
cana-1621	42	43	the	the	DET
cana-1621	42	44	framework	framework	NOUN
cana-1621	42	45	of	of	ADP
cana-1621	42	46	the	the	DET
cana-1621	42	47	proposed	propose	VERB
cana-1621	42	48	model	model	NOUN
cana-1621	42	49	,	,	PUNCT
cana-1621	42	50	frequent	frequent	ADJ
cana-1621	42	51	selection	selection	NOUN
cana-1621	42	52	methods	method	NOUN
cana-1621	42	53	used	use	VERB
cana-1621	42	54	,	,	PUNCT
cana-1621	42	55	rank	rank	NOUN
cana-1621	42	56	aggregation	aggregation	NOUN
cana-1621	42	57	methods	method	NOUN
cana-1621	42	58	used	use	VERB
cana-1621	42	59	and	and	CCONJ
cana-1621	42	60	classification	classification	NOUN
cana-1621	42	61	algorithms	algorithm	NOUN
cana-1621	42	62	.	.	PUNCT
cana-1621	43	1	ensemble	ensemble	ADJ
cana-1621	43	2	feature	feature	NOUN
cana-1621	43	3	ranking	rank	VERB
cana-1621	43	4	3.1	3.1	NUM
cana-1621	43	5	framework	framework	NOUN
cana-1621	43	6	of	of	ADP
cana-1621	43	7	the	the	DET
cana-1621	43	8	proposed	propose	VERB
cana-1621	43	9	model	model	NOUN
cana-1621	43	10	in	in	ADP
cana-1621	43	11	this	this	DET
cana-1621	43	12	study	study	NOUN
cana-1621	43	13	,	,	PUNCT
cana-1621	43	14	a	a	DET
cana-1621	43	15	hybrid	hybrid	ADJ
cana-1621	43	16	feature	feature	NOUN
cana-1621	43	17	selection	selection	NOUN
cana-1621	43	18	(	(	PUNCT
cana-1621	43	19	hfs	hfs	PROPN
cana-1621	43	20	)	)	PUNCT
cana-1621	43	21	method	method	NOUN
cana-1621	43	22	that	that	PRON
cana-1621	43	23	combines	combine	VERB
cana-1621	43	24	the	the	DET
cana-1621	43	25	filters	filter	NOUN
cana-1621	43	26	and	and	CCONJ
cana-1621	43	27	wrappers	wrapper	NOUN
cana-1621	43	28	methods	method	NOUN
cana-1621	43	29	of	of	ADP
cana-1621	43	30	feature	feature	NOUN
cana-1621	43	31	selection	selection	NOUN
cana-1621	43	32	is	be	AUX
cana-1621	43	33	applied	apply	VERB
cana-1621	43	34	.	.	PUNCT
cana-1621	44	1	in	in	ADP
cana-1621	44	2	the	the	DET
cana-1621	44	3	first	first	ADJ
cana-1621	44	4	phase	phase	NOUN
cana-1621	44	5	,	,	PUNCT
cana-1621	44	6	the	the	DET
cana-1621	44	7	features	feature	NOUN
cana-1621	44	8	are	be	AUX
cana-1621	44	9	ranked	rank	VERB
cana-1621	44	10	using	use	VERB
cana-1621	44	11	different	different	ADJ
cana-1621	44	12	filter	filter	NOUN
cana-1621	44	13	-	-	PUNCT
cana-1621	44	14	based	base	VERB
cana-1621	44	15	ranking	ranking	ADJ
cana-1621	44	16	algorithms	algorithm	NOUN
cana-1621	44	17	like	like	ADP
cana-1621	44	18	information	information	NOUN
cana-1621	44	19	gain	gain	NOUN
cana-1621	44	20	,	,	PUNCT
cana-1621	44	21	chi	chi	NOUN
cana-1621	44	22	-	-	PUNCT
cana-1621	44	23	square	square	ADJ
cana-1621	44	24	,	,	PUNCT
cana-1621	44	25	fisher	fisher	PROPN
cana-1621	44	26	score	score	NOUN
cana-1621	44	27	and	and	CCONJ
cana-1621	44	28	brouta	brouta	ADJ
cana-1621	44	29	.	.	PUNCT
cana-1621	45	1	to	to	PART
cana-1621	45	2	select	select	VERB
cana-1621	45	3	features	feature	NOUN
cana-1621	45	4	and	and	CCONJ
cana-1621	45	5	pool	pool	NOUN
cana-1621	45	6	feature	feature	NOUN
cana-1621	45	7	performance	performance	NOUN
cana-1621	45	8	,	,	PUNCT
cana-1621	45	9	a	a	DET
cana-1621	45	10	hybrid	hybrid	ADJ
cana-1621	45	11	feature	feature	NOUN
cana-1621	45	12	selection	selection	NOUN
cana-1621	45	13	technique	technique	NOUN
cana-1621	45	14	currently	currently	ADV
cana-1621	45	15	uses	use	VERB
cana-1621	45	16	a	a	DET
cana-1621	45	17	single	single	ADJ
cana-1621	45	18	rank	rank	NOUN
cana-1621	45	19	aggregation	aggregation	NOUN
cana-1621	45	20	algorithm	algorithm	NOUN
cana-1621	45	21	.	.	PUNCT
cana-1621	46	1	so	so	ADV
cana-1621	46	2	in	in	ADP
cana-1621	46	3	the	the	DET
cana-1621	46	4	second	second	ADJ
cana-1621	46	5	phase	phase	NOUN
cana-1621	46	6	of	of	ADP
cana-1621	46	7	this	this	DET
cana-1621	46	8	study	study	NOUN
cana-1621	46	9	we	we	PRON
cana-1621	46	10	used	use	VERB
cana-1621	46	11	ra	ra	PROPN
cana-1621	46	12	algorithms	algorithm	NOUN
cana-1621	46	13	like	like	ADP
cana-1621	46	14	mc4	mc4	PROPN
cana-1621	46	15	,	,	PUNCT
cana-1621	46	16	random	random	ADJ
cana-1621	46	17	dictator	dictator	NOUN
cana-1621	46	18	using	use	VERB
cana-1621	46	19	kendall	kendall	PROPN
cana-1621	46	20	tau	tau	PROPN
cana-1621	46	21	distance	distance	NOUN
cana-1621	46	22	and	and	CCONJ
cana-1621	46	23	borda	borda	NOUN
cana-1621	46	24	to	to	PART
cana-1621	46	25	combine	combine	VERB
cana-1621	46	26	the	the	DET
cana-1621	46	27	result	result	NOUN
cana-1621	46	28	obtained	obtain	VERB
cana-1621	46	29	from	from	ADP
cana-1621	46	30	different	different	ADJ
cana-1621	46	31	feature	feature	NOUN
cana-1621	46	32	selection	selection	NOUN
cana-1621	46	33	methods	method	NOUN
cana-1621	46	34	.	.	PUNCT
cana-1621	47	1	however	however	ADV
cana-1621	47	2	,	,	PUNCT
cana-1621	47	3	a	a	DET
cana-1621	47	4	single	single	ADJ
cana-1621	47	5	rank	rank	NOUN
cana-1621	47	6	aggregation	aggregation	NOUN
cana-1621	47	7	approach	approach	NOUN
cana-1621	47	8	might	might	AUX
cana-1621	47	9	not	not	PART
cana-1621	47	10	necessarily	necessarily	ADV
cana-1621	47	11	provide	provide	VERB
cana-1621	47	12	the	the	DET
cana-1621	47	13	best	good	ADJ
cana-1621	47	14	results	result	NOUN
cana-1621	47	15	for	for	ADP
cana-1621	47	16	all	all	DET
cana-1621	47	17	datasets	dataset	NOUN
cana-1621	47	18	.	.	PUNCT
cana-1621	48	1	so	so	ADV
cana-1621	48	2	in	in	ADP
cana-1621	48	3	the	the	DET
cana-1621	48	4	third	third	ADJ
cana-1621	48	5	phase	phase	NOUN
cana-1621	48	6	,	,	PUNCT
cana-1621	48	7	this	this	DET
cana-1621	48	8	study	study	NOUN
cana-1621	48	9	uses	use	VERB
cana-1621	48	10	a	a	DET
cana-1621	48	11	new	new	ADJ
cana-1621	48	12	hybrid	hybrid	ADJ
cana-1621	48	13	feature	feature	NOUN
cana-1621	48	14	selection	selection	NOUN
cana-1621	48	15	through	through	ADP
cana-1621	48	16	ensemble	ensemble	ADJ
cana-1621	48	17	rank	rank	NOUN
cana-1621	48	18	aggregation	aggregation	NOUN
cana-1621	48	19	(	(	PUNCT
cana-1621	48	20	hfsera	hfsera	NOUN
cana-1621	48	21	)	)	PUNCT
cana-1621	48	22	to	to	PART
cana-1621	48	23	improve	improve	VERB
cana-1621	48	24	the	the	DET
cana-1621	48	25	selection	selection	NOUN
cana-1621	48	26	of	of	ADP
cana-1621	48	27	features	feature	NOUN
cana-1621	48	28	based	base	VERB
cana-1621	48	29	on	on	ADP
cana-1621	48	30	their	their	PRON
cana-1621	48	31	relative	relative	ADJ
cana-1621	48	32	importance	importance	NOUN
cana-1621	48	33	to	to	ADP
cana-1621	48	34	various	various	ADJ
cana-1621	48	35	ra	ra	PROPN
cana-1621	48	36	strategies	strategy	NOUN
cana-1621	48	37	.	.	PUNCT
cana-1621	49	1	in	in	ADP
cana-1621	49	2	the	the	DET
cana-1621	49	3	last	last	ADJ
cana-1621	49	4	phase	phase	NOUN
cana-1621	49	5	,	,	PUNCT
cana-1621	49	6	a	a	DET
cana-1621	49	7	wrapper	wrapper	NOUN
cana-1621	49	8	method	method	NOUN
cana-1621	49	9	is	be	AUX
cana-1621	49	10	applied	apply	VERB
cana-1621	49	11	to	to	PART
cana-1621	49	12	obtain	obtain	VERB
cana-1621	49	13	the	the	DET
cana-1621	49	14	optimal	optimal	ADJ
cana-1621	49	15	subset	subset	NOUN
cana-1621	49	16	for	for	ADP
cana-1621	49	17	classification	classification	NOUN
cana-1621	49	18	.	.	PUNCT
cana-1621	50	1	algorithm	algorithm	NOUN
cana-1621	50	2	1	1	NUM
cana-1621	50	3	.	.	PUNCT
cana-1621	50	4	start	start	VERB
cana-1621	50	5	with	with	ADP
cana-1621	50	6	dataset	dataset	ADJ
cana-1621	50	7	d	d	NOUN
cana-1621	50	8	with	with	ADP
cana-1621	50	9	p	p	NOUN
cana-1621	50	10	features	feature	NOUN
cana-1621	50	11	.	.	PUNCT
cana-1621	51	1	2	2	X
cana-1621	51	2	.	.	X
cana-1621	51	3	apply	apply	VERB
cana-1621	51	4	filter	filter	NOUN
cana-1621	51	5	-	-	PUNCT
cana-1621	51	6	based	base	VERB
cana-1621	51	7	feature	feature	NOUN
cana-1621	51	8	selection	selection	NOUN
cana-1621	51	9	to	to	PART
cana-1621	51	10	get	get	VERB
cana-1621	51	11	feature	feature	NOUN
cana-1621	51	12	rank	rank	NOUN
cana-1621	51	13	vector	vector	NOUN
cana-1621	51	14	r	r	NOUN
cana-1621	51	15	=	=	PUNCT
cana-1621	51	16	{	{	PUNCT
cana-1621	51	17	r1	r1	PROPN
cana-1621	51	18	,	,	PUNCT
cana-1621	51	19	r2	r2	PROPN
cana-1621	51	20	…	…	SYM
cana-1621	51	21	…	…	SYM
cana-1621	51	22	rn	rn	NOUN
cana-1621	51	23	}	}	PUNCT
cana-1621	51	24	3	3	NUM
cana-1621	51	25	.	.	PUNCT
cana-1621	51	26	apply	apply	VERB
cana-1621	51	27	n	n	DET
cana-1621	51	28	rank	rank	NOUN
cana-1621	51	29	aggregation	aggregation	NOUN
cana-1621	51	30	to	to	PART
cana-1621	51	31	get	get	AUX
cana-1621	51	32	aggregated	aggregate	VERB
cana-1621	51	33	rank	rank	PROPN
cana-1621	51	34	ar	ar	PROPN
cana-1621	51	35	=	=	PRON
cana-1621	51	36	{	{	PUNCT
cana-1621	51	37	r1	r1	PROPN
cana-1621	51	38	,	,	PUNCT
cana-1621	51	39	r2,	r2,	NOUN
cana-1621	51	40	…	…	SYM
cana-1621	51	41	.rp	.rp	SYM
cana-1621	51	42	}	}	PUNCT
cana-1621	51	43	communications	communication	NOUN
cana-1621	51	44	on	on	ADP
cana-1621	51	45	applied	apply	VERB
cana-1621	51	46	nonlinear	nonlinear	ADJ
cana-1621	51	47	analysis	analysis	NOUN
cana-1621	51	48	issn	issn	NOUN
cana-1621	51	49	:	:	PUNCT
cana-1621	51	50	1074	1074	NUM
cana-1621	51	51	-	-	PUNCT
cana-1621	51	52	133x	133x	NUM
cana-1621	51	53	vol	vol	NOUN
cana-1621	51	54	32	32	NUM
cana-1621	51	55	no	no	NOUN
cana-1621	51	56	.	.	NOUN
cana-1621	51	57	1	1	NUM
cana-1621	51	58	(	(	PUNCT
cana-1621	51	59	2025	2025	NUM
cana-1621	51	60	)	)	PUNCT
cana-1621	51	61	65	65	NUM
cana-1621	51	62	https://internationalpubls.com	https://internationalpubls.com	X
cana-1621	51	63	4	4	X
cana-1621	51	64	.	.	NOUN
cana-1621	52	1	combine	combine	PROPN
cana-1621	52	2	aggregated	aggregate	VERB
cana-1621	52	3	rank	rank	PROPN
cana-1621	52	4	ar1	ar1	PROPN
cana-1621	52	5	,	,	PUNCT
cana-1621	52	6	ar2	ar2	PROPN
cana-1621	52	7	…	…	PUNCT
cana-1621	52	8	..	..	PUNCT
cana-1621	52	9	arn	arn	NOUN
cana-1621	52	10	by	by	ADP
cana-1621	52	11	using	use	VERB
cana-1621	52	12	ensemble	ensemble	ADJ
cana-1621	52	13	rank	rank	NOUN
cana-1621	52	14	aggregation	aggregation	NOUN
cana-1621	52	15	.	.	PUNCT
cana-1621	53	1	5	5	X
cana-1621	53	2	.	.	X
cana-1621	53	3	use	use	NOUN
cana-1621	53	4	wrapper	wrapper	NOUN
cana-1621	53	5	method	method	NOUN
cana-1621	53	6	to	to	PART
cana-1621	53	7	get	get	VERB
cana-1621	53	8	the	the	DET
cana-1621	53	9	optimum	optimum	ADJ
cana-1621	53	10	result	result	NOUN
cana-1621	53	11	.	.	PUNCT
cana-1621	54	1	3.2	3.2	NUM
cana-1621	54	2	feature	feature	NOUN
cana-1621	54	3	selection	selection	NOUN
cana-1621	54	4	methods	method	NOUN
cana-1621	54	5	frequent	frequent	ADJ
cana-1621	54	6	selection	selection	NOUN
cana-1621	54	7	strategies	strategy	NOUN
cana-1621	54	8	have	have	VERB
cana-1621	54	9	the	the	DET
cana-1621	54	10	potential	potential	NOUN
cana-1621	54	11	to	to	PART
cana-1621	54	12	improve	improve	VERB
cana-1621	54	13	classifier	classifier	ADJ
cana-1621	54	14	accuracy	accuracy	NOUN
cana-1621	54	15	while	while	SCONJ
cana-1621	54	16	simultaneously	simultaneously	ADV
cana-1621	54	17	reducing	reduce	VERB
cana-1621	54	18	computational	computational	ADJ
cana-1621	54	19	costs	cost	NOUN
cana-1621	54	20	by	by	ADP
cana-1621	54	21	removing	remove	VERB
cana-1621	54	22	obtrusive	obtrusive	ADJ
cana-1621	54	23	and	and	CCONJ
cana-1621	54	24	distracting	distract	VERB
cana-1621	54	25	characteristics	characteristic	NOUN
cana-1621	54	26	.	.	PUNCT
cana-1621	55	1	supervised	supervised	ADJ
cana-1621	55	2	learning	learning	NOUN
cana-1621	55	3	and	and	CCONJ
cana-1621	55	4	unsupervised	unsupervised	ADJ
cana-1621	55	5	learning	learning	NOUN
cana-1621	55	6	are	be	AUX
cana-1621	55	7	the	the	DET
cana-1621	55	8	two	two	NUM
cana-1621	55	9	categories	category	NOUN
cana-1621	55	10	used	use	VERB
cana-1621	55	11	to	to	PART
cana-1621	55	12	categorise	categorise	VERB
cana-1621	55	13	feature	feature	NOUN
cana-1621	55	14	selection	selection	NOUN
cana-1621	55	15	techniques	technique	NOUN
cana-1621	55	16	.	.	PUNCT
cana-1621	56	1	for	for	ADP
cana-1621	56	2	the	the	DET
cana-1621	56	3	purpose	purpose	NOUN
cana-1621	56	4	of	of	ADP
cana-1621	56	5	locating	locate	VERB
cana-1621	56	6	pertinent	pertinent	ADJ
cana-1621	56	7	information	information	NOUN
cana-1621	56	8	,	,	PUNCT
cana-1621	56	9	supervised	supervise	VERB
cana-1621	56	10	learning	learning	NOUN
cana-1621	56	11	makes	make	VERB
cana-1621	56	12	use	use	NOUN
cana-1621	56	13	of	of	ADP
cana-1621	56	14	labelled	label	VERB
cana-1621	56	15	data	datum	NOUN
cana-1621	56	16	while	while	SCONJ
cana-1621	56	17	unsupervised	unsupervised	ADJ
cana-1621	56	18	learning	learning	NOUN
cana-1621	56	19	makes	make	VERB
cana-1621	56	20	use	use	NOUN
cana-1621	56	21	of	of	ADP
cana-1621	56	22	unlabelled	unlabelled	ADJ
cana-1621	56	23	data	datum	NOUN
cana-1621	56	24	.	.	PUNCT
cana-1621	57	1	filter	filter	NOUN
cana-1621	57	2	,	,	PUNCT
cana-1621	57	3	wrapper	wrapper	NOUN
cana-1621	57	4	,	,	PUNCT
cana-1621	57	5	and	and	CCONJ
cana-1621	57	6	embedding	embed	VERB
cana-1621	57	7	methods	method	NOUN
cana-1621	57	8	are	be	AUX
cana-1621	57	9	once	once	ADV
cana-1621	57	10	more	more	ADV
cana-1621	57	11	divided	divide	VERB
cana-1621	57	12	under	under	ADP
cana-1621	57	13	the	the	DET
cana-1621	57	14	category	category	NOUN
cana-1621	57	15	of	of	ADP
cana-1621	57	16	supervised	supervised	ADJ
cana-1621	57	17	methods	method	NOUN
cana-1621	57	18	.	.	PUNCT
cana-1621	58	1	in	in	ADP
cana-1621	58	2	this	this	DET
cana-1621	58	3	work	work	NOUN
cana-1621	58	4	,	,	PUNCT
cana-1621	58	5	infogain	infogain	NOUN
cana-1621	58	6	,	,	PUNCT
cana-1621	58	7	fisherscore	fisherscore	ADJ
cana-1621	58	8	,	,	PUNCT
cana-1621	58	9	chisquare	chisquare	NOUN
cana-1621	58	10	,	,	PUNCT
cana-1621	58	11	ref	ref	NOUN
cana-1621	58	12	and	and	CCONJ
cana-1621	58	13	brouta	brouta	ADV
cana-1621	58	14	are	be	AUX
cana-1621	58	15	used	use	VERB
cana-1621	58	16	for	for	ADP
cana-1621	58	17	feature	feature	NOUN
cana-1621	58	18	subset	subset	NOUN
cana-1621	58	19	selection	selection	NOUN
cana-1621	58	20	.	.	PUNCT
cana-1621	59	1	3.2.1	3.2.1	NUM
cana-1621	59	2	information	information	NOUN
cana-1621	59	3	gain	gain	NOUN
cana-1621	59	4	to	to	PART
cana-1621	59	5	determine	determine	VERB
cana-1621	59	6	the	the	DET
cana-1621	59	7	reduction	reduction	NOUN
cana-1621	59	8	in	in	ADP
cana-1621	59	9	entropy	entropy	NOUN
cana-1621	59	10	or	or	CCONJ
cana-1621	59	11	surprise	surprise	NOUN
cana-1621	59	12	,	,	PUNCT
cana-1621	59	13	information	information	NOUN
cana-1621	59	14	gain	gain	NOUN
cana-1621	59	15	divides	divide	VERB
cana-1621	59	16	a	a	DET
cana-1621	59	17	dataset	dataset	NOUN
cana-1621	59	18	according	accord	VERB
cana-1621	59	19	to	to	ADP
cana-1621	59	20	a	a	DET
cana-1621	59	21	given	give	VERB
cana-1621	59	22	value	value	NOUN
cana-1621	59	23	of	of	ADP
cana-1621	59	24	a	a	DET
cana-1621	59	25	random	random	ADJ
cana-1621	59	26	variable	variable	NOUN
cana-1621	59	27	.	.	PUNCT
cana-1621	60	1	less	less	ADJ
cana-1621	60	2	surprise	surprise	NOUN
cana-1621	60	3	results	result	NOUN
cana-1621	60	4	from	from	ADP
cana-1621	60	5	lower	low	ADJ
cana-1621	60	6	entropy	entropy	NOUN
cana-1621	60	7	groups	group	NOUN
cana-1621	60	8	of	of	ADP
cana-1621	60	9	samples	sample	NOUN
cana-1621	60	10	,	,	PUNCT
cana-1621	60	11	which	which	PRON
cana-1621	60	12	are	be	AUX
cana-1621	60	13	what	what	PRON
cana-1621	60	14	larger	large	ADJ
cana-1621	60	15	information	information	NOUN
cana-1621	60	16	gains	gain	NOUN
cana-1621	60	17	suggest	suggest	VERB
cana-1621	60	18	[	[	X
cana-1621	60	19	13	13	NUM
cana-1621	60	20	]	]	PUNCT
cana-1621	60	21	.	.	PUNCT
cana-1621	61	1	mathematical	mathematical	ADJ
cana-1621	61	2	formula	formula	NOUN
cana-1621	61	3	of	of	ADP
cana-1621	61	4	an	an	DET
cana-1621	61	5	entropy	entropy	NOUN
cana-1621	61	6	is	be	AUX
cana-1621	61	7	h(x	h(x	PROPN
cana-1621	61	8	)	)	PUNCT
cana-1621	62	1	=	=	SYM
cana-1621	62	2	-∑pi	-∑pi	PROPN
cana-1621	62	3	log2	log2	NOUN
cana-1621	62	4	(	(	PUNCT
cana-1621	62	5	pi	pi	NOUN
cana-1621	62	6	)	)	PUNCT
cana-1621	62	7	here	here	ADV
cana-1621	62	8	‘	'	PUNCT
cana-1621	62	9	i	i	PRON
cana-1621	62	10	’	'	PUNCT
cana-1621	62	11	is	be	AUX
cana-1621	62	12	the	the	DET
cana-1621	62	13	total	total	ADJ
cana-1621	62	14	number	number	NOUN
cana-1621	62	15	of	of	ADP
cana-1621	62	16	values	value	NOUN
cana-1621	62	17	that	that	PRON
cana-1621	62	18	x	x	PRON
cana-1621	62	19	can	can	AUX
cana-1621	62	20	take	take	VERB
cana-1621	62	21	.	.	PUNCT
cana-1621	63	1	in	in	ADP
cana-1621	63	2	this	this	DET
cana-1621	63	3	method	method	NOUN
cana-1621	63	4	,	,	PUNCT
cana-1621	63	5	the	the	DET
cana-1621	63	6	information	information	NOUN
cana-1621	63	7	gain	gain	NOUN
cana-1621	63	8	(	(	PUNCT
cana-1621	63	9	ig	ig	PROPN
cana-1621	63	10	)	)	PUNCT
cana-1621	63	11	for	for	ADP
cana-1621	63	12	each	each	DET
cana-1621	63	13	attribute	attribute	NOUN
cana-1621	63	14	is	be	AUX
cana-1621	63	15	calculated	calculate	VERB
cana-1621	63	16	.	.	PUNCT
cana-1621	64	1	after	after	ADP
cana-1621	64	2	this	this	PRON
cana-1621	64	3	,	,	PUNCT
cana-1621	64	4	by	by	ADP
cana-1621	64	5	using	use	VERB
cana-1621	64	6	ig	ig	PRON
cana-1621	64	7	the	the	DET
cana-1621	64	8	attributes	attribute	NOUN
cana-1621	64	9	will	will	AUX
cana-1621	64	10	rank	rank	VERB
cana-1621	64	11	in	in	ADP
cana-1621	64	12	decreasing	decrease	VERB
cana-1621	64	13	order	order	NOUN
cana-1621	64	14	.	.	PUNCT
cana-1621	65	1	mathematically	mathematically	ADV
cana-1621	65	2	,	,	PUNCT
cana-1621	65	3	information	information	NOUN
cana-1621	65	4	gain	gain	NOUN
cana-1621	65	5	is	be	AUX
cana-1621	65	6	defined	define	VERB
cana-1621	65	7	as	as	ADP
cana-1621	65	8	,	,	PUNCT
cana-1621	65	9	ig(y	ig(y	NOUN
cana-1621	65	10	/	/	SYM
cana-1621	65	11	x	x	NOUN
cana-1621	65	12	)	)	PUNCT
cana-1621	65	13	=	=	SYM
cana-1621	65	14	h(y	h(y	ADV
cana-1621	65	15	)	)	PUNCT
cana-1621	65	16	h(y	h(y	ADV
cana-1621	65	17	/	/	SYM
cana-1621	65	18	x	x	X
cana-1621	65	19	)	)	PUNCT
cana-1621	65	20	3.2.2	3.2.2	NUM
cana-1621	65	21	chi	chi	PROPN
cana-1621	65	22	square	square	ADJ
cana-1621	65	23	chi	chi	PROPN
cana-1621	65	24	-	-	PUNCT
cana-1621	65	25	square	square	NOUN
cana-1621	65	26	is	be	AUX
cana-1621	65	27	one	one	NUM
cana-1621	65	28	of	of	ADP
cana-1621	65	29	the	the	DET
cana-1621	65	30	commonly	commonly	ADV
cana-1621	65	31	used	use	VERB
cana-1621	65	32	method	method	NOUN
cana-1621	65	33	for	for	ADP
cana-1621	65	34	feature	feature	NOUN
cana-1621	65	35	selection	selection	NOUN
cana-1621	65	36	.	.	PUNCT
cana-1621	66	1	it	it	PRON
cana-1621	66	2	is	be	AUX
cana-1621	66	3	a	a	DET
cana-1621	66	4	statistical	statistical	ADJ
cana-1621	66	5	test	test	NOUN
cana-1621	66	6	of	of	ADP
cana-1621	66	7	independence	independence	NOUN
cana-1621	66	8	to	to	PART
cana-1621	66	9	determine	determine	VERB
cana-1621	66	10	the	the	DET
cana-1621	66	11	dependency	dependency	NOUN
cana-1621	66	12	of	of	ADP
cana-1621	66	13	two	two	NUM
cana-1621	66	14	variables	variable	NOUN
cana-1621	66	15	.	.	PUNCT
cana-1621	67	1	the	the	DET
cana-1621	67	2	formula	formula	NOUN
cana-1621	67	3	for	for	ADP
cana-1621	67	4	chi	chi	NOUN
cana-1621	67	5	-	-	PUNCT
cana-1621	67	6	square	square	NOUN
cana-1621	67	7	is	be	AUX
cana-1621	67	8	where	where	SCONJ
cana-1621	67	9	o	o	NOUN
cana-1621	67	10	observed	observe	VERB
cana-1621	67	11	value	value	NOUN
cana-1621	67	12	e	e	NOUN
cana-1621	67	13	exceted	excete	VERB
cana-1621	67	14	value	value	NOUN
cana-1621	67	15	c	c	NOUN
cana-1621	67	16	degree	degree	NOUN
cana-1621	67	17	of	of	ADP
cana-1621	67	18	freedom	freedom	NOUN
cana-1621	67	19	when	when	SCONJ
cana-1621	67	20	two	two	NUM
cana-1621	67	21	features	feature	NOUN
cana-1621	67	22	are	be	AUX
cana-1621	67	23	distinct	distinct	ADJ
cana-1621	67	24	from	from	ADP
cana-1621	67	25	one	one	NUM
cana-1621	67	26	another	another	DET
cana-1621	67	27	,	,	PUNCT
cana-1621	67	28	the	the	DET
cana-1621	67	29	observed	observed	ADJ
cana-1621	67	30	count	count	NOUN
cana-1621	67	31	is	be	AUX
cana-1621	67	32	nearly	nearly	ADV
cana-1621	67	33	identical	identical	ADJ
cana-1621	67	34	to	to	ADP
cana-1621	67	35	the	the	DET
cana-1621	67	36	predicted	predict	VERB
cana-1621	67	37	count	count	NOUN
cana-1621	67	38	,	,	PUNCT
cana-1621	67	39	resulting	result	VERB
cana-1621	67	40	in	in	ADP
cana-1621	67	41	a	a	DET
cana-1621	67	42	lower	low	ADJ
cana-1621	67	43	chi	chi	ADJ
cana-1621	67	44	-	-	PUNCT
cana-1621	67	45	square	square	ADJ
cana-1621	67	46	value	value	NOUN
cana-1621	67	47	.	.	PUNCT
cana-1621	68	1	the	the	DET
cana-1621	68	2	features	feature	NOUN
cana-1621	68	3	with	with	ADP
cana-1621	68	4	higher	high	ADJ
cana-1621	68	5	chi	chi	ADJ
cana-1621	68	6	-	-	PUNCT
cana-1621	68	7	square	square	ADJ
cana-1621	68	8	value	value	NOUN
cana-1621	68	9	is	be	AUX
cana-1621	68	10	chosen	choose	VERB
cana-1621	68	11	for	for	ADP
cana-1621	68	12	model	model	NOUN
cana-1621	68	13	training	training	NOUN
cana-1621	68	14	because	because	SCONJ
cana-1621	68	15	it	it	PRON
cana-1621	68	16	depends	depend	VERB
cana-1621	68	17	more	more	ADJ
cana-1621	68	18	on	on	ADP
cana-1621	68	19	the	the	DET
cana-1621	68	20	response	response	NOUN
cana-1621	68	21	.	.	PUNCT
cana-1621	69	1	the	the	DET
cana-1621	69	2	following	follow	VERB
cana-1621	69	3	are	be	AUX
cana-1621	69	4	the	the	DET
cana-1621	69	5	steps	step	NOUN
cana-1621	69	6	used	use	VERB
cana-1621	69	7	in	in	ADP
cana-1621	69	8	chi	chi	ADJ
cana-1621	69	9	-	-	PUNCT
cana-1621	69	10	square	square	ADJ
cana-1621	69	11	test	test	NOUN
cana-1621	69	12	:	:	PUNCT
cana-1621	69	13	▪	▪	X
cana-1621	69	14	define	define	VERB
cana-1621	69	15	hypothesis	hypothesis	NOUN
cana-1621	69	16	.	.	PUNCT
cana-1621	70	1	▪	▪	X
cana-1621	70	2	create	create	VERB
cana-1621	70	3	a	a	DET
cana-1621	70	4	contingency	contingency	NOUN
cana-1621	70	5	table	table	NOUN
cana-1621	70	6	.	.	PUNCT
cana-1621	71	1	▪	▪	NOUN
cana-1621	71	2	locate	locate	VERB
cana-1621	71	3	the	the	DET
cana-1621	71	4	expected	expect	VERB
cana-1621	71	5	values	value	NOUN
cana-1621	71	6	.	.	PUNCT
cana-1621	72	1	▪	▪	NOUN
cana-1621	72	2	determine	determine	VERB
cana-1621	72	3	the	the	DET
cana-1621	72	4	chi	chi	ADJ
cana-1621	72	5	-	-	PUNCT
cana-1621	72	6	square	square	ADJ
cana-1621	72	7	statistic	statistic	NOUN
cana-1621	72	8	.	.	PUNCT
cana-1621	73	1	▪	▪	NOUN
cana-1621	73	2	accept	accept	VERB
cana-1621	73	3	or	or	CCONJ
cana-1621	73	4	reject	reject	VERB
cana-1621	73	5	the	the	DET
cana-1621	73	6	null	null	ADJ
cana-1621	73	7	hypothesis	hypothesis	NOUN
cana-1621	73	8	.	.	PUNCT
cana-1621	74	1	communications	communication	NOUN
cana-1621	74	2	on	on	ADP
cana-1621	74	3	applied	apply	VERB
cana-1621	74	4	nonlinear	nonlinear	ADJ
cana-1621	74	5	analysis	analysis	NOUN
cana-1621	74	6	issn	issn	NOUN
cana-1621	74	7	:	:	PUNCT
cana-1621	74	8	1074	1074	NUM
cana-1621	74	9	-	-	PUNCT
cana-1621	74	10	133x	133x	NUM
cana-1621	74	11	vol	vol	NOUN
cana-1621	74	12	32	32	NUM
cana-1621	74	13	no	no	NOUN
cana-1621	74	14	.	.	NOUN
cana-1621	74	15	1	1	NUM
cana-1621	74	16	(	(	PUNCT
cana-1621	74	17	2025	2025	NUM
cana-1621	74	18	)	)	PUNCT
cana-1621	74	19	66	66	NUM
cana-1621	74	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1621	74	21	3.2.3	3.2.3	NUM
cana-1621	74	22	fisher	fisher	PROPN
cana-1621	74	23	score	score	NOUN
cana-1621	74	24	fisher	fisher	PROPN
cana-1621	74	25	score	score	NOUN
cana-1621	74	26	is	be	AUX
cana-1621	74	27	a	a	DET
cana-1621	74	28	supervised	supervised	ADJ
cana-1621	74	29	feature	feature	NOUN
cana-1621	74	30	selection	selection	NOUN
cana-1621	74	31	method	method	NOUN
cana-1621	74	32	and	and	CCONJ
cana-1621	74	33	it	it	PRON
cana-1621	74	34	returns	return	VERB
cana-1621	74	35	the	the	DET
cana-1621	74	36	variables	variable	NOUN
cana-1621	74	37	'	'	PART
cana-1621	74	38	ranks	rank	NOUN
cana-1621	74	39	based	base	VERB
cana-1621	74	40	on	on	ADP
cana-1621	74	41	the	the	DET
cana-1621	74	42	fisher	fisher	PROPN
cana-1621	74	43	score	score	NOUN
cana-1621	74	44	in	in	ADP
cana-1621	74	45	descending	descend	VERB
cana-1621	74	46	order	order	NOUN
cana-1621	74	47	.	.	PUNCT
cana-1621	75	1	with	with	ADP
cana-1621	75	2	the	the	DET
cana-1621	75	3	use	use	NOUN
cana-1621	75	4	of	of	ADP
cana-1621	75	5	supervised	supervised	ADJ
cana-1621	75	6	learning	learning	NOUN
cana-1621	75	7	for	for	ADP
cana-1621	75	8	feature	feature	NOUN
cana-1621	75	9	selection	selection	NOUN
cana-1621	75	10	,	,	PUNCT
cana-1621	75	11	fisher	fisher	PROPN
cana-1621	75	12	score	score	NOUN
cana-1621	75	13	models	model	NOUN
cana-1621	75	14	have	have	VERB
cana-1621	75	15	several	several	ADJ
cana-1621	75	16	benefits	benefit	NOUN
cana-1621	75	17	,	,	PUNCT
cana-1621	75	18	including	include	VERB
cana-1621	75	19	fewer	few	ADJ
cana-1621	75	20	calculations	calculation	NOUN
cana-1621	75	21	,	,	PUNCT
cana-1621	75	22	greater	great	ADJ
cana-1621	75	23	accuracy	accuracy	NOUN
cana-1621	75	24	,	,	PUNCT
cana-1621	75	25	and	and	CCONJ
cana-1621	75	26	stronger	strong	ADJ
cana-1621	75	27	operability	operability	NOUN
cana-1621	75	28	,	,	PUNCT
cana-1621	75	29	which	which	PRON
cana-1621	75	30	can	can	AUX
cana-1621	75	31	effectively	effectively	ADV
cana-1621	75	32	reduce	reduce	VERB
cana-1621	75	33	time	time	NOUN
cana-1621	75	34	-	-	PUNCT
cana-1621	75	35	space	space	NOUN
cana-1621	75	36	complexity	complexity	NOUN
cana-1621	75	37	[	[	X
cana-1621	75	38	14	14	NUM
cana-1621	75	39	]	]	PUNCT
cana-1621	75	40	.	.	PUNCT
cana-1621	76	1	3.2.4	3.2.4	NUM
cana-1621	76	2	brouta	brouta	ADV
cana-1621	76	3	brouta	brouta	ADV
cana-1621	76	4	,	,	PUNCT
cana-1621	76	5	a	a	DET
cana-1621	76	6	random	random	ADJ
cana-1621	76	7	forest	forest	NOUN
cana-1621	76	8	-	-	PUNCT
cana-1621	76	9	based	base	VERB
cana-1621	76	10	approach	approach	NOUN
cana-1621	76	11	that	that	PRON
cana-1621	76	12	removes	remove	VERB
cana-1621	76	13	features	feature	NOUN
cana-1621	76	14	that	that	PRON
cana-1621	76	15	are	be	AUX
cana-1621	76	16	statistically	statistically	ADV
cana-1621	76	17	less	less	ADV
cana-1621	76	18	relevant	relevant	ADJ
cana-1621	76	19	.	.	PUNCT
cana-1621	77	1	variables	variable	NOUN
cana-1621	77	2	that	that	PRON
cana-1621	77	3	are	be	AUX
cana-1621	77	4	rejected	reject	VERB
cana-1621	77	5	in	in	ADP
cana-1621	77	6	one	one	NUM
cana-1621	77	7	iteration	iteration	NOUN
cana-1621	77	8	are	be	AUX
cana-1621	77	9	not	not	PART
cana-1621	77	10	taken	take	VERB
cana-1621	77	11	into	into	ADP
cana-1621	77	12	account	account	NOUN
cana-1621	77	13	in	in	ADP
cana-1621	77	14	the	the	DET
cana-1621	77	15	following	follow	VERB
cana-1621	77	16	iteration	iteration	NOUN
cana-1621	77	17	.	.	PUNCT
cana-1621	78	1	initially	initially	ADV
cana-1621	78	2	,	,	PUNCT
cana-1621	78	3	brouta	brouta	ADV
cana-1621	78	4	creates	create	VERB
cana-1621	78	5	shadow	shadow	NOUN
cana-1621	78	6	features	feature	NOUN
cana-1621	78	7	by	by	ADP
cana-1621	78	8	randomly	randomly	ADV
cana-1621	78	9	shuffling	shuffle	VERB
cana-1621	78	10	the	the	DET
cana-1621	78	11	features	feature	NOUN
cana-1621	78	12	.	.	PUNCT
cana-1621	79	1	then	then	ADV
cana-1621	79	2	it	it	PRON
cana-1621	79	3	evaluate	evaluate	VERB
cana-1621	79	4	the	the	DET
cana-1621	79	5	importance	importance	NOUN
cana-1621	79	6	of	of	ADP
cana-1621	79	7	each	each	DET
cana-1621	79	8	features	feature	NOUN
cana-1621	79	9	and	and	CCONJ
cana-1621	79	10	check	check	VERB
cana-1621	79	11	whether	whether	SCONJ
cana-1621	79	12	these	these	DET
cana-1621	79	13	features	feature	NOUN
cana-1621	79	14	have	have	VERB
cana-1621	79	15	higher	high	ADJ
cana-1621	79	16	score	score	NOUN
cana-1621	79	17	than	than	SCONJ
cana-1621	79	18	the	the	DET
cana-1621	79	19	maximum	maximum	ADJ
cana-1621	79	20	score	score	NOUN
cana-1621	79	21	of	of	ADP
cana-1621	79	22	its	its	PRON
cana-1621	79	23	shadow	shadow	NOUN
cana-1621	79	24	features	feature	VERB
cana-1621	79	25	or	or	CCONJ
cana-1621	79	26	not	not	PART
cana-1621	79	27	.	.	PUNCT
cana-1621	80	1	immediately	immediately	ADV
cana-1621	80	2	it	it	PRON
cana-1621	80	3	removes	remove	VERB
cana-1621	80	4	the	the	DET
cana-1621	80	5	unimportant	unimportant	ADJ
cana-1621	80	6	features	feature	NOUN
cana-1621	80	7	.	.	PUNCT
cana-1621	81	1	finally	finally	ADV
cana-1621	81	2	,	,	PUNCT
cana-1621	81	3	the	the	DET
cana-1621	81	4	method	method	NOUN
cana-1621	81	5	terminates	terminate	VERB
cana-1621	81	6	either	either	CCONJ
cana-1621	81	7	when	when	SCONJ
cana-1621	81	8	all	all	DET
cana-1621	81	9	features	feature	NOUN
cana-1621	81	10	are	be	AUX
cana-1621	81	11	accepted	accept	VERB
cana-1621	81	12	or	or	CCONJ
cana-1621	81	13	rejected	reject	VERB
cana-1621	81	14	or	or	CCONJ
cana-1621	81	15	when	when	SCONJ
cana-1621	81	16	the	the	DET
cana-1621	81	17	number	number	NOUN
cana-1621	81	18	of	of	ADP
cana-1621	81	19	random	random	ADJ
cana-1621	81	20	forest	forest	NOUN
cana-1621	81	21	runs	run	NOUN
cana-1621	81	22	reaches	reach	VERB
cana-1621	81	23	a	a	DET
cana-1621	81	24	predetermined	predetermined	ADJ
cana-1621	81	25	threshold	threshold	NOUN
cana-1621	81	26	.	.	PUNCT
cana-1621	82	1	3.2.4	3.2.4	NUM
cana-1621	82	2	recursive	recursive	ADJ
cana-1621	82	3	feature	feature	NOUN
cana-1621	82	4	elimination	elimination	NOUN
cana-1621	82	5	(	(	PUNCT
cana-1621	82	6	rfe	rfe	NOUN
cana-1621	82	7	)	)	PUNCT
cana-1621	82	8	rfe	rfe	NOUN
cana-1621	82	9	is	be	AUX
cana-1621	82	10	an	an	DET
cana-1621	82	11	effective	effective	ADJ
cana-1621	82	12	wrapper	wrapper	NOUN
cana-1621	82	13	method	method	NOUN
cana-1621	82	14	for	for	ADP
cana-1621	82	15	feature	feature	NOUN
cana-1621	82	16	selection	selection	NOUN
cana-1621	82	17	method	method	NOUN
cana-1621	82	18	because	because	SCONJ
cana-1621	82	19	it	it	PRON
cana-1621	82	20	selects	select	VERB
cana-1621	82	21	features	feature	NOUN
cana-1621	82	22	that	that	PRON
cana-1621	82	23	are	be	AUX
cana-1621	82	24	most	most	ADV
cana-1621	82	25	useful	useful	ADJ
cana-1621	82	26	for	for	ADP
cana-1621	82	27	predicting	predict	VERB
cana-1621	82	28	the	the	DET
cana-1621	82	29	target	target	NOUN
cana-1621	82	30	variable	variable	NOUN
cana-1621	82	31	.	.	PUNCT
cana-1621	83	1	using	use	VERB
cana-1621	83	2	all	all	PRON
cana-1621	83	3	of	of	ADP
cana-1621	83	4	the	the	DET
cana-1621	83	5	features	feature	NOUN
cana-1621	83	6	in	in	ADP
cana-1621	83	7	the	the	DET
cana-1621	83	8	training	training	NOUN
cana-1621	83	9	dataset	dataset	NOUN
cana-1621	83	10	as	as	ADP
cana-1621	83	11	a	a	DET
cana-1621	83	12	starting	starting	NOUN
cana-1621	83	13	point	point	NOUN
cana-1621	83	14	,	,	PUNCT
cana-1621	83	15	rfe	rfe	NOUN
cana-1621	83	16	attempts	attempt	NOUN
cana-1621	83	17	to	to	PART
cana-1621	83	18	find	find	VERB
cana-1621	83	19	a	a	DET
cana-1621	83	20	subset	subset	NOUN
cana-1621	83	21	of	of	ADP
cana-1621	83	22	features	feature	NOUN
cana-1621	83	23	by	by	ADP
cana-1621	83	24	successfully	successfully	ADV
cana-1621	83	25	deleting	delete	VERB
cana-1621	83	26	features	feature	NOUN
cana-1621	83	27	one	one	NUM
cana-1621	83	28	at	at	ADP
cana-1621	83	29	a	a	DET
cana-1621	83	30	time	time	NOUN
cana-1621	83	31	until	until	SCONJ
cana-1621	83	32	the	the	DET
cana-1621	83	33	target	target	NOUN
cana-1621	83	34	number	number	NOUN
cana-1621	83	35	of	of	ADP
cana-1621	83	36	features	feature	NOUN
cana-1621	83	37	is	be	AUX
cana-1621	83	38	left	leave	VERB
cana-1621	83	39	.	.	PUNCT
cana-1621	84	1	this	this	PRON
cana-1621	84	2	is	be	AUX
cana-1621	84	3	accomplished	accomplish	VERB
cana-1621	84	4	by	by	ADP
cana-1621	84	5	first	first	ADV
cana-1621	84	6	fitting	fit	VERB
cana-1621	84	7	the	the	DET
cana-1621	84	8	core	core	NOUN
cana-1621	84	9	model	model	NOUN
cana-1621	84	10	's	's	PART
cana-1621	84	11	machine	machine	NOUN
cana-1621	84	12	learning	learning	NOUN
cana-1621	84	13	algorithm	algorithm	NOUN
cana-1621	84	14	,	,	PUNCT
cana-1621	84	15	ranking	rank	VERB
cana-1621	84	16	the	the	DET
cana-1621	84	17	features	feature	NOUN
cana-1621	84	18	according	accord	VERB
cana-1621	84	19	to	to	ADP
cana-1621	84	20	relevance	relevance	NOUN
cana-1621	84	21	,	,	PUNCT
cana-1621	84	22	eliminating	eliminate	VERB
cana-1621	84	23	the	the	DET
cana-1621	84	24	least	least	ADV
cana-1621	84	25	important	important	ADJ
cana-1621	84	26	features	feature	NOUN
cana-1621	84	27	,	,	PUNCT
cana-1621	84	28	and	and	CCONJ
cana-1621	84	29	then	then	ADV
cana-1621	84	30	re	re	VERB
cana-1621	84	31	-	-	VERB
cana-1621	84	32	fitting	fit	VERB
cana-1621	84	33	the	the	DET
cana-1621	84	34	model	model	NOUN
cana-1621	84	35	.	.	PUNCT
cana-1621	85	1	up	up	ADV
cana-1621	85	2	until	until	SCONJ
cana-1621	85	3	a	a	DET
cana-1621	85	4	certain	certain	ADJ
cana-1621	85	5	amount	amount	NOUN
cana-1621	85	6	of	of	ADP
cana-1621	85	7	traits	trait	NOUN
cana-1621	85	8	are	be	AUX
cana-1621	85	9	still	still	ADV
cana-1621	85	10	present	present	ADJ
cana-1621	85	11	,	,	PUNCT
cana-1621	85	12	this	this	DET
cana-1621	85	13	process	process	NOUN
cana-1621	85	14	is	be	AUX
cana-1621	85	15	repeated	repeat	VERB
cana-1621	85	16	[	[	PUNCT
cana-1621	85	17	10	10	NUM
cana-1621	85	18	]	]	PUNCT
cana-1621	85	19	.	.	PUNCT
cana-1621	86	1	3.3	3.3	NUM
cana-1621	86	2	rank	rank	NOUN
cana-1621	86	3	aggregation	aggregation	NOUN
cana-1621	86	4	methods	method	NOUN
cana-1621	86	5	rank	rank	NOUN
cana-1621	86	6	aggregation	aggregation	NOUN
cana-1621	86	7	methods	method	NOUN
cana-1621	86	8	uses	use	VERB
cana-1621	86	9	the	the	DET
cana-1621	86	10	rank	rank	NOUN
cana-1621	86	11	list	list	NOUN
cana-1621	86	12	generated	generate	VERB
cana-1621	86	13	by	by	ADP
cana-1621	86	14	different	different	ADJ
cana-1621	86	15	algorithms	algorithm	NOUN
cana-1621	86	16	as	as	ADP
cana-1621	86	17	inputs	input	NOUN
cana-1621	86	18	and	and	CCONJ
cana-1621	86	19	it	it	PRON
cana-1621	86	20	produces	produce	VERB
cana-1621	86	21	another	another	DET
cana-1621	86	22	rank	rank	NOUN
cana-1621	86	23	list	list	NOUN
cana-1621	86	24	as	as	ADP
cana-1621	86	25	output	output	NOUN
cana-1621	86	26	.	.	PUNCT
cana-1621	87	1	different	different	ADJ
cana-1621	87	2	rank	rank	NOUN
cana-1621	87	3	aggregation	aggregation	NOUN
cana-1621	87	4	algorithms	algorithm	NOUN
cana-1621	87	5	can	can	AUX
cana-1621	87	6	be	be	AUX
cana-1621	87	7	used	use	VERB
cana-1621	87	8	to	to	PART
cana-1621	87	9	combine	combine	VERB
cana-1621	87	10	the	the	DET
cana-1621	87	11	base	base	NOUN
cana-1621	87	12	input	input	NOUN
cana-1621	87	13	ranking	ranking	NOUN
cana-1621	87	14	features	feature	NOUN
cana-1621	87	15	.	.	PUNCT
cana-1621	88	1	they	they	PRON
cana-1621	88	2	are	be	AUX
cana-1621	88	3	3.3.1	3.3.1	NUM
cana-1621	88	4	markov	markov	NOUN
cana-1621	88	5	chain	chain	NOUN
cana-1621	88	6	type	type	NOUN
cana-1621	88	7	4	4	NUM
cana-1621	88	8	or	or	CCONJ
cana-1621	88	9	mc4	mc4	PROPN
cana-1621	88	10	a	a	DET
cana-1621	88	11	markov	markov	NOUN
cana-1621	88	12	chain	chain	NOUN
cana-1621	88	13	essentially	essentially	ADV
cana-1621	88	14	consists	consist	VERB
cana-1621	88	15	of	of	ADP
cana-1621	88	16	a	a	DET
cana-1621	88	17	sequence	sequence	NOUN
cana-1621	88	18	of	of	ADP
cana-1621	88	19	transitions	transition	NOUN
cana-1621	88	20	that	that	PRON
cana-1621	88	21	meet	meet	VERB
cana-1621	88	22	the	the	DET
cana-1621	88	23	markov	markov	NOUN
cana-1621	88	24	property	property	NOUN
cana-1621	88	25	and	and	CCONJ
cana-1621	88	26	are	be	AUX
cana-1621	88	27	specified	specify	VERB
cana-1621	88	28	by	by	ADP
cana-1621	88	29	some	some	DET
cana-1621	88	30	probability	probability	NOUN
cana-1621	88	31	distribution	distribution	NOUN
cana-1621	88	32	.	.	PUNCT
cana-1621	89	1	in	in	ADP
cana-1621	89	2	the	the	DET
cana-1621	89	3	markov	markov	NOUN
cana-1621	89	4	chain	chain	NOUN
cana-1621	89	5	methods	method	NOUN
cana-1621	89	6	for	for	ADP
cana-1621	89	7	ranked	rank	VERB
cana-1621	89	8	list	list	NOUN
cana-1621	89	9	aggregation	aggregation	NOUN
cana-1621	89	10	,	,	PUNCT
cana-1621	89	11	the	the	DET
cana-1621	89	12	items	item	NOUN
cana-1621	89	13	in	in	ADP
cana-1621	89	14	the	the	DET
cana-1621	89	15	various	various	ADJ
cana-1621	89	16	lists	list	NOUN
cana-1621	89	17	are	be	AUX
cana-1621	89	18	represented	represent	VERB
cana-1621	89	19	as	as	ADP
cana-1621	89	20	nodes	node	NOUN
cana-1621	89	21	in	in	ADP
cana-1621	89	22	a	a	DET
cana-1621	89	23	graph	graph	NOUN
cana-1621	89	24	,	,	PUNCT
cana-1621	89	25	with	with	ADP
cana-1621	89	26	the	the	DET
cana-1621	89	27	probability	probability	NOUN
cana-1621	89	28	of	of	ADP
cana-1621	89	29	transitions	transition	NOUN
cana-1621	89	30	from	from	ADP
cana-1621	89	31	node	node	NOUN
cana-1621	89	32	to	to	ADP
cana-1621	89	33	node	node	NOUN
cana-1621	89	34	being	be	AUX
cana-1621	89	35	determined	determine	VERB
cana-1621	89	36	by	by	ADP
cana-1621	89	37	the	the	DET
cana-1621	89	38	relative	relative	ADJ
cana-1621	89	39	rankings	ranking	NOUN
cana-1621	89	40	of	of	ADP
cana-1621	89	41	the	the	DET
cana-1621	89	42	items	item	NOUN
cana-1621	89	43	in	in	ADP
cana-1621	89	44	the	the	DET
cana-1621	89	45	various	various	ADJ
cana-1621	89	46	lists	list	NOUN
cana-1621	89	47	[	[	X
cana-1621	89	48	11	11	NUM
cana-1621	89	49	]	]	PUNCT
cana-1621	89	50	.	.	PUNCT
cana-1621	90	1	a	a	DET
cana-1621	90	2	transition	transition	NOUN
cana-1621	90	3	matrix	matrix	NOUN
cana-1621	90	4	is	be	AUX
cana-1621	90	5	used	use	VERB
cana-1621	90	6	to	to	PART
cana-1621	90	7	represent	represent	VERB
cana-1621	90	8	the	the	DET
cana-1621	90	9	probability	probability	NOUN
cana-1621	90	10	distribution	distribution	NOUN
cana-1621	90	11	of	of	ADP
cana-1621	90	12	state	state	NOUN
cana-1621	90	13	transitions	transition	NOUN
cana-1621	90	14	.	.	PUNCT
cana-1621	91	1	this	this	DET
cana-1621	91	2	matrix	matrix	NOUN
cana-1621	91	3	is	be	AUX
cana-1621	91	4	a	a	DET
cana-1621	91	5	stochastic	stochastic	ADJ
cana-1621	91	6	matrix	matrix	NOUN
cana-1621	91	7	,	,	PUNCT
cana-1621	91	8	each	each	DET
cana-1621	91	9	cell(i	cell(i	PROPN
cana-1621	91	10	,	,	PUNCT
cana-1621	91	11	j	j	NOUN
cana-1621	91	12	)	)	PUNCT
cana-1621	91	13	of	of	ADP
cana-1621	91	14	this	this	DET
cana-1621	91	15	matrix	matrix	NOUN
cana-1621	91	16	represents	represent	VERB
cana-1621	91	17	the	the	DET
cana-1621	91	18	probability	probability	NOUN
cana-1621	91	19	of	of	ADP
cana-1621	91	20	transition	transition	NOUN
cana-1621	91	21	from	from	ADP
cana-1621	91	22	state	state	NOUN
cana-1621	91	23	i	i	PRON
cana-1621	91	24	to	to	ADP
cana-1621	91	25	jmarkov	jmarkov	PROPN
cana-1621	91	26	chain	chain	NOUN
cana-1621	91	27	also	also	ADV
cana-1621	91	28	uses	use	VERB
cana-1621	91	29	an	an	DET
cana-1621	91	30	mx1	mx1	PROPN
cana-1621	91	31	vector	vector	NOUN
cana-1621	91	32	called	call	VERB
cana-1621	91	33	initial	initial	ADJ
cana-1621	91	34	state	state	NOUN
cana-1621	91	35	vector	vector	NOUN
cana-1621	91	36	used	use	VERB
cana-1621	91	37	to	to	PART
cana-1621	91	38	mention	mention	VERB
cana-1621	91	39	the	the	DET
cana-1621	91	40	probability	probability	NOUN
cana-1621	91	41	distribution	distribution	NOUN
cana-1621	91	42	of	of	ADP
cana-1621	91	43	starting	start	VERB
cana-1621	91	44	at	at	ADP
cana-1621	91	45	each	each	PRON
cana-1621	91	46	of	of	ADP
cana-1621	91	47	the	the	DET
cana-1621	91	48	n	n	CCONJ
cana-1621	91	49	possible	possible	ADJ
cana-1621	91	50	states	state	NOUN
cana-1621	91	51	[	[	X
cana-1621	91	52	12	12	NUM
cana-1621	91	53	]	]	X
cana-1621	91	54	..	..	PUNCT
cana-1621	91	55	3.3.2	3.3.2	NUM
cana-1621	91	56	random	random	ADJ
cana-1621	91	57	dictator	dictator	NOUN
cana-1621	91	58	through	through	ADP
cana-1621	91	59	kendall	kendall	PROPN
cana-1621	91	60	tau	tau	PROPN
cana-1621	91	61	distance	distance	NOUN
cana-1621	91	62	the	the	DET
cana-1621	91	63	kendall	kendall	PROPN
cana-1621	91	64	tau	tau	PROPN
cana-1621	91	65	distance	distance	NOUN
cana-1621	91	66	measures	measure	NOUN
cana-1621	91	67	the	the	DET
cana-1621	91	68	number	number	NOUN
cana-1621	91	69	of	of	ADP
cana-1621	91	70	disagreements	disagreement	NOUN
cana-1621	91	71	between	between	ADP
cana-1621	91	72	two	two	NUM
cana-1621	91	73	ranking	ranking	ADJ
cana-1621	91	74	lists	list	NOUN
cana-1621	91	75	.	.	PUNCT
cana-1621	92	1	the	the	DET
cana-1621	92	2	kendall	kendall	PROPN
cana-1621	92	3	tau	tau	PROPN
cana-1621	92	4	distance	distance	NOUN
cana-1621	92	5	between	between	ADP
cana-1621	92	6	two	two	NUM
cana-1621	92	7	lists	list	NOUN
cana-1621	92	8	la	la	NOUN
cana-1621	92	9	and	and	CCONJ
cana-1621	92	10	lb	lb	NUM
cana-1621	92	11	is	be	AUX
cana-1621	92	12	:	:	PUNCT
cana-1621	92	13	k	k	X
cana-1621	92	14	(	(	PUNCT
cana-1621	92	15	la	la	PROPN
cana-1621	92	16	,	,	PUNCT
cana-1621	92	17	lb	lb	NOUN
cana-1621	92	18	)	)	PUNCT
cana-1621	92	19	=	=	SYM
cana-1621	93	1	|	|	INTJ
cana-1621	93	2	(	(	PUNCT
cana-1621	93	3	i	i	NOUN
cana-1621	93	4	,	,	PUNCT
cana-1621	93	5	j	j	PROPN
cana-1621	93	6	)	)	PUNCT
cana-1621	93	7	:	:	PUNCT
cana-1621	94	1	i	i	PRON
cana-1621	94	2	<	<	X
cana-1621	94	3	j	j	PROPN
cana-1621	94	4	,	,	PUNCT
cana-1621	94	5	(	(	PUNCT
cana-1621	94	6	la	la	X
cana-1621	94	7	(	(	PUNCT
cana-1621	94	8	i	i	NOUN
cana-1621	94	9	)	)	PUNCT
cana-1621	94	10	<	<	X
cana-1621	94	11	la	la	PROPN
cana-1621	94	12	(	(	PUNCT
cana-1621	94	13	j	j	PROPN
cana-1621	94	14	)	)	PUNCT
cana-1621	94	15	∧	∧	NOUN
cana-1621	94	16	lb	lb	ADP
cana-1621	94	17	(	(	PUNCT
cana-1621	94	18	i	i	NOUN
cana-1621	94	19	)	)	PUNCT
cana-1621	94	20	>	>	X
cana-1621	95	1	lb	lb	X
cana-1621	95	2	(	(	PUNCT
cana-1621	95	3	j	j	NOUN
cana-1621	95	4	)	)	PUNCT
cana-1621	95	5	)	)	PUNCT
cana-1621	96	1	v	v	X
cana-1621	96	2	(	(	PUNCT
cana-1621	96	3	la	la	X
cana-1621	96	4	(	(	PUNCT
cana-1621	96	5	i	i	NOUN
cana-1621	96	6	)	)	PUNCT
cana-1621	96	7	>	>	X
cana-1621	97	1	la	la	X
cana-1621	97	2	(	(	PUNCT
cana-1621	97	3	j	j	PROPN
cana-1621	97	4	)	)	PUNCT
cana-1621	97	5	∧	∧	NOUN
cana-1621	97	6	lb	lb	X
cana-1621	97	7	(	(	PUNCT
cana-1621	97	8	i	i	NOUN
cana-1621	97	9	)	)	PUNCT
cana-1621	97	10	<	<	X
cana-1621	98	1	lb	lb	X
cana-1621	98	2	(	(	PUNCT
cana-1621	98	3	j	j	NOUN
cana-1621	98	4	)	)	PUNCT
cana-1621	98	5	)	)	PUNCT
cana-1621	99	1	|	|	ADV
cana-1621	99	2	k(la	k(la	PROPN
cana-1621	99	3	,	,	PUNCT
cana-1621	99	4	lb	lb	X
cana-1621	99	5	)	)	PUNCT
cana-1621	99	6	will	will	AUX
cana-1621	99	7	be	be	AUX
cana-1621	99	8	equal	equal	ADJ
cana-1621	99	9	to	to	ADP
cana-1621	99	10	0	0	NUM
cana-1621	99	11	if	if	SCONJ
cana-1621	99	12	the	the	DET
cana-1621	99	13	two	two	NUM
cana-1621	99	14	lists	list	NOUN
cana-1621	99	15	are	be	AUX
cana-1621	99	16	identical	identical	ADJ
cana-1621	99	17	and	and	CCONJ
cana-1621	99	18	n(n-1)/2	n(n-1)/2	PROPN
cana-1621	99	19	(	(	PUNCT
cana-1621	99	20	where	where	SCONJ
cana-1621	99	21	n	n	X
cana-1621	99	22	is	be	AUX
cana-1621	99	23	the	the	DET
cana-1621	99	24	list	list	NOUN
cana-1621	99	25	size	size	NOUN
cana-1621	99	26	)	)	PUNCT
cana-1621	99	27	if	if	SCONJ
cana-1621	99	28	one	one	NUM
cana-1621	99	29	list	list	NOUN
cana-1621	99	30	is	be	AUX
cana-1621	99	31	the	the	DET
cana-1621	99	32	reverse	reverse	NOUN
cana-1621	99	33	of	of	ADP
cana-1621	99	34	the	the	DET
cana-1621	99	35	other	other	ADJ
cana-1621	99	36	.	.	PUNCT
cana-1621	100	1	other	other	ADJ
cana-1621	100	2	formula	formula	NOUN
cana-1621	100	3	used	use	VERB
cana-1621	100	4	for	for	ADP
cana-1621	100	5	kendall	kendall	PROPN
cana-1621	100	6	tau	tau	PROPN
cana-1621	100	7	is	be	AUX
cana-1621	100	8	:	:	PUNCT
cana-1621	100	9	communications	communication	NOUN
cana-1621	100	10	on	on	ADP
cana-1621	100	11	applied	apply	VERB
cana-1621	100	12	nonlinear	nonlinear	ADJ
cana-1621	100	13	analysis	analysis	NOUN
cana-1621	100	14	issn	issn	NOUN
cana-1621	100	15	:	:	PUNCT
cana-1621	100	16	1074	1074	NUM
cana-1621	100	17	-	-	PUNCT
cana-1621	100	18	133x	133x	NUM
cana-1621	100	19	vol	vol	NOUN
cana-1621	100	20	32	32	NUM
cana-1621	100	21	no	no	NOUN
cana-1621	100	22	.	.	NOUN
cana-1621	100	23	1	1	NUM
cana-1621	100	24	(	(	PUNCT
cana-1621	100	25	2025	2025	NUM
cana-1621	100	26	)	)	PUNCT
cana-1621	100	27	67	67	NUM
cana-1621	100	28	https://internationalpubls.com	https://internationalpubls.com	X
cana-1621	100	29	where	where	SCONJ
cana-1621	100	30	3.2.3	3.2.3	NUM
cana-1621	100	31	bordas	bordas	PROPN
cana-1621	100	32	rank	rank	NOUN
cana-1621	100	33	aggregation	aggregation	NOUN
cana-1621	100	34	a	a	DET
cana-1621	100	35	set	set	NOUN
cana-1621	100	36	of	of	ADP
cana-1621	100	37	positional	positional	ADJ
cana-1621	100	38	voting	voting	NOUN
cana-1621	100	39	guidelines	guideline	NOUN
cana-1621	100	40	known	know	VERB
cana-1621	100	41	as	as	ADP
cana-1621	100	42	the	the	DET
cana-1621	100	43	borda	borda	PROPN
cana-1621	100	44	count	count	PROPN
cana-1621	100	45	assigns	assign	NOUN
cana-1621	100	46	each	each	DET
cana-1621	100	47	candidate	candidate	NOUN
cana-1621	100	48	a	a	DET
cana-1621	100	49	certain	certain	ADJ
cana-1621	100	50	number	number	NOUN
cana-1621	100	51	of	of	ADP
cana-1621	100	52	points	point	NOUN
cana-1621	100	53	for	for	ADP
cana-1621	100	54	each	each	DET
cana-1621	100	55	ballot	ballot	NOUN
cana-1621	100	56	based	base	VERB
cana-1621	100	57	on	on	ADP
cana-1621	100	58	how	how	SCONJ
cana-1621	100	59	many	many	ADJ
cana-1621	100	60	candidates	candidate	NOUN
cana-1621	100	61	are	be	AUX
cana-1621	100	62	placed	place	VERB
cana-1621	100	63	lower	low	ADJ
cana-1621	100	64	than	than	ADP
cana-1621	100	65	them	they	PRON
cana-1621	100	66	.	.	PUNCT
cana-1621	101	1	the	the	DET
cana-1621	101	2	highest	highest	ADV
cana-1621	101	3	-	-	PUNCT
cana-1621	101	4	ranked	rank	VERB
cana-1621	101	5	candidate	candidate	NOUN
cana-1621	101	6	receives	receive	VERB
cana-1621	101	7	n	n	PRON
cana-1621	101	8	1	1	NUM
cana-1621	101	9	points	point	NOUN
cana-1621	101	10	,	,	PUNCT
cana-1621	101	11	where	where	SCONJ
cana-1621	101	12	n	n	PRON
cana-1621	101	13	is	be	AUX
cana-1621	101	14	the	the	DET
cana-1621	101	15	number	number	NOUN
cana-1621	101	16	of	of	ADP
cana-1621	101	17	candidates	candidate	NOUN
cana-1621	101	18	,	,	PUNCT
cana-1621	101	19	in	in	ADP
cana-1621	101	20	the	the	DET
cana-1621	101	21	original	original	ADJ
cana-1621	101	22	form	form	NOUN
cana-1621	101	23	,	,	PUNCT
cana-1621	101	24	the	the	DET
cana-1621	101	25	lowestranked	lowestranked	ADJ
cana-1621	101	26	candidate	candidate	NOUN
cana-1621	101	27	receives	receive	VERB
cana-1621	101	28	0	0	NUM
cana-1621	101	29	points	point	NOUN
cana-1621	101	30	,	,	PUNCT
cana-1621	101	31	the	the	DET
cana-1621	101	32	next	next	ADV
cana-1621	101	33	-	-	PUNCT
cana-1621	101	34	lowest	low	ADJ
cana-1621	101	35	receives	receive	VERB
cana-1621	101	36	1	1	NUM
cana-1621	101	37	point	point	NOUN
cana-1621	101	38	,	,	PUNCT
cana-1621	101	39	etc	etc	X
cana-1621	101	40	.	.	X
cana-1621	102	1	the	the	DET
cana-1621	102	2	choice	choice	NOUN
cana-1621	102	3	or	or	CCONJ
cana-1621	102	4	candidate	candidate	NOUN
cana-1621	102	5	with	with	ADP
cana-1621	102	6	the	the	DET
cana-1621	102	7	most	most	ADJ
cana-1621	102	8	points	point	NOUN
cana-1621	102	9	after	after	SCONJ
cana-1621	102	10	the	the	DET
cana-1621	102	11	results	result	NOUN
cana-1621	102	12	of	of	ADP
cana-1621	102	13	all	all	DET
cana-1621	102	14	votes	vote	NOUN
cana-1621	102	15	are	be	AUX
cana-1621	102	16	tallied	tally	VERB
cana-1621	102	17	wins	win	NOUN
cana-1621	102	18	[	[	X
cana-1621	102	19	15	15	NUM
cana-1621	102	20	]	]	PUNCT
cana-1621	102	21	.	.	PUNCT
cana-1621	103	1	the	the	DET
cana-1621	103	2	borda	borda	NOUN
cana-1621	103	3	count	count	NOUN
cana-1621	103	4	is	be	AUX
cana-1621	103	5	frequently	frequently	ADV
cana-1621	103	6	referred	refer	VERB
cana-1621	103	7	to	to	PART
cana-1621	103	8	be	be	AUX
cana-1621	103	9	a	a	DET
cana-1621	103	10	consensus	consensus	NOUN
cana-1621	103	11	-	-	PUNCT
cana-1621	103	12	based	base	VERB
cana-1621	103	13	voting	voting	NOUN
cana-1621	103	14	method	method	NOUN
cana-1621	103	15	as	as	SCONJ
cana-1621	103	16	opposed	oppose	VERB
cana-1621	103	17	to	to	ADP
cana-1621	103	18	a	a	DET
cana-1621	103	19	majoritarian	majoritarian	ADJ
cana-1621	103	20	one	one	NOUN
cana-1621	103	21	because	because	SCONJ
cana-1621	103	22	it	it	PRON
cana-1621	103	23	aims	aim	VERB
cana-1621	103	24	to	to	PART
cana-1621	103	25	elect	elect	VERB
cana-1621	103	26	broadly	broadly	ADV
cana-1621	103	27	acceptable	acceptable	ADJ
cana-1621	103	28	options	option	NOUN
cana-1621	103	29	or	or	CCONJ
cana-1621	103	30	candidates	candidate	NOUN
cana-1621	103	31	rather	rather	ADV
cana-1621	103	32	than	than	ADP
cana-1621	103	33	those	those	PRON
cana-1621	103	34	that	that	PRON
cana-1621	103	35	are	be	AUX
cana-1621	103	36	favoured	favour	VERB
cana-1621	103	37	by	by	ADP
cana-1621	103	38	the	the	DET
cana-1621	103	39	majority	majority	NOUN
cana-1621	103	40	.	.	PUNCT
cana-1621	104	1	[	[	X
cana-1621	104	2	16	16	NUM
cana-1621	104	3	]	]	SYM
cana-1621	104	4	3.4	3.4	NUM
cana-1621	104	5	classification	classification	NOUN
cana-1621	104	6	algorithms	algorithm	NOUN
cana-1621	104	7	in	in	ADP
cana-1621	104	8	this	this	DET
cana-1621	104	9	study	study	NOUN
cana-1621	104	10	random	random	ADJ
cana-1621	104	11	forest	forest	NOUN
cana-1621	104	12	is	be	AUX
cana-1621	104	13	used	use	VERB
cana-1621	104	14	for	for	ADP
cana-1621	104	15	classification	classification	NOUN
cana-1621	104	16	due	due	ADP
cana-1621	104	17	to	to	ADP
cana-1621	104	18	its	its	PRON
cana-1621	104	19	high	high	ADJ
cana-1621	104	20	efficiency	efficiency	NOUN
cana-1621	104	21	.	.	PUNCT
cana-1621	105	1	3.4.1	3.4.1	NUM
cana-1621	105	2	random	random	ADJ
cana-1621	105	3	forest	forest	NOUN
cana-1621	105	4	random	random	ADJ
cana-1621	105	5	forest	forest	NOUN
cana-1621	105	6	is	be	AUX
cana-1621	105	7	a	a	DET
cana-1621	105	8	supervised	supervised	ADJ
cana-1621	105	9	machine	machine	NOUN
cana-1621	105	10	learning	learning	NOUN
cana-1621	105	11	algorithm	algorithm	NOUN
cana-1621	105	12	used	use	VERB
cana-1621	105	13	for	for	ADP
cana-1621	105	14	classification	classification	NOUN
cana-1621	105	15	and	and	CCONJ
cana-1621	105	16	regression	regression	NOUN
cana-1621	105	17	.	.	PUNCT
cana-1621	106	1	these	these	DET
cana-1621	106	2	classifiers	classifier	NOUN
cana-1621	106	3	handle	handle	VERB
cana-1621	106	4	the	the	DET
cana-1621	106	5	missing	miss	VERB
cana-1621	106	6	values	value	NOUN
cana-1621	106	7	and	and	CCONJ
cana-1621	106	8	can	can	AUX
cana-1621	106	9	model	model	VERB
cana-1621	106	10	the	the	DET
cana-1621	106	11	categorical	categorical	ADJ
cana-1621	106	12	values	value	NOUN
cana-1621	106	13	.	.	PUNCT
cana-1621	107	1	it	it	PRON
cana-1621	107	2	creates	create	VERB
cana-1621	107	3	many	many	ADJ
cana-1621	107	4	decision	decision	NOUN
cana-1621	107	5	trees	tree	NOUN
cana-1621	107	6	and	and	CCONJ
cana-1621	107	7	merges	merge	VERB
cana-1621	107	8	them	they	PRON
cana-1621	107	9	together	together	ADV
cana-1621	107	10	to	to	PART
cana-1621	107	11	form	form	VERB
cana-1621	107	12	an	an	DET
cana-1621	107	13	accurate	accurate	ADJ
cana-1621	107	14	prediction	prediction	NOUN
cana-1621	107	15	.	.	PUNCT
cana-1621	108	1	in	in	ADP
cana-1621	108	2	the	the	DET
cana-1621	108	3	method	method	NOUN
cana-1621	108	4	the	the	DET
cana-1621	108	5	parameters	parameter	NOUN
cana-1621	108	6	are	be	AUX
cana-1621	108	7	used	use	VERB
cana-1621	108	8	to	to	PART
cana-1621	108	9	increase	increase	VERB
cana-1621	108	10	the	the	DET
cana-1621	108	11	predictive	predictive	ADJ
cana-1621	108	12	power	power	NOUN
cana-1621	108	13	and	and	CCONJ
cana-1621	108	14	speed	speed	NOUN
cana-1621	108	15	of	of	ADP
cana-1621	108	16	the	the	DET
cana-1621	108	17	model	model	NOUN
cana-1621	108	18	.	.	PUNCT
cana-1621	109	1	the	the	DET
cana-1621	109	2	advantages	advantage	NOUN
cana-1621	109	3	of	of	ADP
cana-1621	109	4	random	random	ADJ
cana-1621	109	5	forest	forest	NOUN
cana-1621	109	6	:	:	PUNCT
cana-1621	109	7	▪	▪	ADJ
cana-1621	109	8	both	both	CCONJ
cana-1621	109	9	classification	classification	NOUN
cana-1621	109	10	and	and	CCONJ
cana-1621	109	11	regression	regression	NOUN
cana-1621	109	12	problems	problem	NOUN
cana-1621	109	13	can	can	AUX
cana-1621	109	14	be	be	AUX
cana-1621	109	15	resolved	resolve	VERB
cana-1621	109	16	using	use	VERB
cana-1621	109	17	random	random	ADJ
cana-1621	109	18	forest	forest	NOUN
cana-1621	109	19	.	.	PUNCT
cana-1621	110	1	▪	▪	NOUN
cana-1621	110	2	handling	handle	VERB
cana-1621	110	3	missing	miss	VERB
cana-1621	110	4	values	value	NOUN
cana-1621	110	5	and	and	CCONJ
cana-1621	110	6	outliers	outlier	NOUN
cana-1621	110	7	automatically	automatically	ADV
cana-1621	110	8	.	.	PUNCT
cana-1621	111	1	▪	▪	ADJ
cana-1621	111	2	random	random	ADJ
cana-1621	111	3	forest	forest	NOUN
cana-1621	111	4	is	be	AUX
cana-1621	111	5	considerably	considerably	ADV
cana-1621	111	6	less	less	ADV
cana-1621	111	7	influenced	influence	VERB
cana-1621	111	8	by	by	ADP
cana-1621	111	9	noise	noise	NOUN
cana-1621	111	10	.	.	PUNCT
cana-1621	112	1	▪	▪	NOUN
cana-1621	112	2	it	it	PRON
cana-1621	112	3	can	can	AUX
cana-1621	112	4	handle	handle	VERB
cana-1621	112	5	categorical	categorical	ADJ
cana-1621	112	6	and	and	CCONJ
cana-1621	112	7	continuous	continuous	ADJ
cana-1621	112	8	variables	variable	NOUN
cana-1621	112	9	.	.	PUNCT
cana-1621	113	1	▪	▪	ADJ
cana-1621	113	2	random	random	ADJ
cana-1621	113	3	forest	forest	NOUN
cana-1621	113	4	is	be	AUX
cana-1621	113	5	comparatively	comparatively	ADV
cana-1621	113	6	less	less	ADV
cana-1621	113	7	affected	affect	VERB
cana-1621	113	8	by	by	ADP
cana-1621	113	9	noise	noise	NOUN
cana-1621	113	10	.	.	PUNCT
cana-1621	114	1	3.5	3.5	NUM
cana-1621	114	2	datasets	dataset	NOUN
cana-1621	114	3	used	use	VERB
cana-1621	114	4	in	in	ADP
cana-1621	114	5	this	this	DET
cana-1621	114	6	study	study	NOUN
cana-1621	114	7	,	,	PUNCT
cana-1621	114	8	we	we	PRON
cana-1621	114	9	have	have	AUX
cana-1621	114	10	used	use	VERB
cana-1621	114	11	two	two	NUM
cana-1621	114	12	sets	set	NOUN
cana-1621	114	13	of	of	ADP
cana-1621	114	14	credit	credit	NOUN
cana-1621	114	15	data	datum	NOUN
cana-1621	114	16	from	from	ADP
cana-1621	114	17	the	the	DET
cana-1621	114	18	uci	uci	PROPN
cana-1621	114	19	repository	repository	NOUN
cana-1621	114	20	.	.	PUNCT
cana-1621	115	1	there	there	PRON
cana-1621	115	2	are	be	VERB
cana-1621	115	3	690	690	NUM
cana-1621	115	4	instances	instance	NOUN
cana-1621	115	5	and	and	CCONJ
cana-1621	115	6	15	15	NUM
cana-1621	115	7	attributes	attribute	NOUN
cana-1621	115	8	in	in	ADP
cana-1621	115	9	the	the	DET
cana-1621	115	10	australian	australian	ADJ
cana-1621	115	11	credit	credit	NOUN
cana-1621	115	12	data	datum	NOUN
cana-1621	115	13	set	set	VERB
cana-1621	115	14	.	.	PUNCT
cana-1621	116	1	a	a	DET
cana-1621	116	2	german	german	ADJ
cana-1621	116	3	credit	credit	NOUN
cana-1621	116	4	data	datum	NOUN
cana-1621	116	5	set	set	VERB
cana-1621	116	6	with	with	ADP
cana-1621	116	7	21	21	NUM
cana-1621	116	8	attributes	attribute	NOUN
cana-1621	116	9	and	and	CCONJ
cana-1621	116	10	1000	1000	NUM
cana-1621	116	11	occurrences	occurrence	NOUN
cana-1621	116	12	makes	make	VERB
cana-1621	116	13	up	up	ADP
cana-1621	116	14	the	the	DET
cana-1621	116	15	second	second	ADJ
cana-1621	116	16	one	one	NUM
cana-1621	116	17	.	.	PUNCT
cana-1621	117	1	four	four	NUM
cana-1621	117	2	feature	feature	NOUN
cana-1621	117	3	selection	selection	NOUN
cana-1621	117	4	techniques	technique	NOUN
cana-1621	117	5	—	—	PUNCT
cana-1621	117	6	chi	chi	ADJ
cana-1621	117	7	-	-	PUNCT
cana-1621	117	8	square	square	ADJ
cana-1621	117	9	,	,	PUNCT
cana-1621	117	10	fisher	fisher	PROPN
cana-1621	117	11	score	score	NOUN
cana-1621	117	12	,	,	PUNCT
cana-1621	117	13	information	information	NOUN
cana-1621	117	14	gain	gain	NOUN
cana-1621	117	15	,	,	PUNCT
cana-1621	117	16	and	and	CCONJ
cana-1621	117	17	boruta	boruta	NOUN
cana-1621	117	18	—	—	PUNCT
cana-1621	117	19	as	as	ADV
cana-1621	117	20	well	well	ADV
cana-1621	117	21	as	as	ADP
cana-1621	117	22	three	three	NUM
cana-1621	117	23	rank	rank	NOUN
cana-1621	117	24	aggregation	aggregation	NOUN
cana-1621	117	25	techniques	technique	NOUN
cana-1621	117	26	—	—	PUNCT
cana-1621	117	27	markov	markov	NOUN
cana-1621	117	28	chain	chain	NOUN
cana-1621	117	29	type	type	NOUN
cana-1621	117	30	4	4	NUM
cana-1621	117	31	or	or	CCONJ
cana-1621	117	32	mc4	mc4	PROPN
cana-1621	117	33	,	,	PUNCT
cana-1621	117	34	borda	borda	NOUN
cana-1621	117	35	count	count	NOUN
cana-1621	117	36	,	,	PUNCT
cana-1621	117	37	and	and	CCONJ
cana-1621	117	38	random	random	ADJ
cana-1621	117	39	dictator	dictator	NOUN
cana-1621	117	40	are	be	AUX
cana-1621	117	41	used	use	VERB
cana-1621	117	42	in	in	ADP
cana-1621	117	43	this	this	DET
cana-1621	117	44	study	study	NOUN
cana-1621	117	45	.	.	PUNCT
cana-1621	118	1	communications	communication	NOUN
cana-1621	118	2	on	on	ADP
cana-1621	118	3	applied	apply	VERB
cana-1621	118	4	nonlinear	nonlinear	ADJ
cana-1621	118	5	analysis	analysis	NOUN
cana-1621	118	6	issn	issn	NOUN
cana-1621	118	7	:	:	PUNCT
cana-1621	118	8	1074	1074	NUM
cana-1621	118	9	-	-	PUNCT
cana-1621	118	10	133x	133x	NUM
cana-1621	118	11	vol	vol	NOUN
cana-1621	118	12	32	32	NUM
cana-1621	118	13	no	no	NOUN
cana-1621	118	14	.	.	NOUN
cana-1621	118	15	1	1	NUM
cana-1621	118	16	(	(	PUNCT
cana-1621	118	17	2025	2025	NUM
cana-1621	118	18	)	)	PUNCT
cana-1621	118	19	68	68	NUM
cana-1621	118	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1621	118	21	4	4	NUM
cana-1621	118	22	.	.	NOUN
cana-1621	118	23	result	result	NOUN
cana-1621	118	24	and	and	CCONJ
cana-1621	118	25	discussion	discussion	NOUN
cana-1621	118	26	although	although	SCONJ
cana-1621	118	27	ensemble	ensemble	ADJ
cana-1621	118	28	feature	feature	NOUN
cana-1621	118	29	selection	selection	NOUN
cana-1621	118	30	through	through	ADP
cana-1621	118	31	rank	rank	NOUN
cana-1621	118	32	aggregation	aggregation	NOUN
cana-1621	118	33	can	can	AUX
cana-1621	118	34	avoid	avoid	VERB
cana-1621	118	35	irrelevant	irrelevant	ADJ
cana-1621	118	36	and	and	CCONJ
cana-1621	118	37	redundant	redundant	ADJ
cana-1621	118	38	information	information	NOUN
cana-1621	118	39	,	,	PUNCT
cana-1621	118	40	hybrid	hybrid	ADJ
cana-1621	118	41	feature	feature	NOUN
cana-1621	118	42	selection	selection	NOUN
cana-1621	118	43	through	through	ADP
cana-1621	118	44	ensemble	ensemble	ADJ
cana-1621	118	45	rank	rank	NOUN
cana-1621	118	46	aggregation	aggregation	NOUN
cana-1621	118	47	can	can	AUX
cana-1621	118	48	make	make	VERB
cana-1621	118	49	classifiers	classifier	NOUN
cana-1621	118	50	more	more	ADV
cana-1621	118	51	efficient	efficient	ADJ
cana-1621	118	52	.	.	PUNCT
cana-1621	119	1	in	in	ADP
cana-1621	119	2	this	this	DET
cana-1621	119	3	study	study	NOUN
cana-1621	119	4	,	,	PUNCT
cana-1621	119	5	the	the	DET
cana-1621	119	6	individual	individual	ADJ
cana-1621	119	7	ranks	rank	NOUN
cana-1621	119	8	lists	list	NOUN
cana-1621	119	9	are	be	AUX
cana-1621	119	10	calculated	calculate	VERB
cana-1621	119	11	using	use	VERB
cana-1621	119	12	fisher	fisher	PROPN
cana-1621	119	13	score	score	NOUN
cana-1621	119	14	,	,	PUNCT
cana-1621	119	15	chi	chi	ADJ
cana-1621	119	16	-	-	PUNCT
cana-1621	119	17	square	square	NOUN
cana-1621	119	18	and	and	CCONJ
cana-1621	119	19	boruta	boruta	NOUN
cana-1621	119	20	.	.	PUNCT
cana-1621	120	1	after	after	ADP
cana-1621	120	2	that	that	PRON
cana-1621	120	3	the	the	DET
cana-1621	120	4	rank	rank	NOUN
cana-1621	120	5	aggregation	aggregation	NOUN
cana-1621	120	6	algorithms	algorithms	PROPN
cana-1621	120	7	mc4	mc4	PROPN
cana-1621	120	8	,	,	PUNCT
cana-1621	120	9	borda	borda	NOUN
cana-1621	120	10	and	and	CCONJ
cana-1621	120	11	random	random	ADJ
cana-1621	120	12	dictator	dictator	NOUN
cana-1621	120	13	are	be	AUX
cana-1621	120	14	used	use	VERB
cana-1621	120	15	to	to	PART
cana-1621	120	16	combine	combine	VERB
cana-1621	120	17	the	the	DET
cana-1621	120	18	multiple	multiple	ADJ
cana-1621	120	19	individually	individually	ADV
cana-1621	120	20	ranked	rank	VERB
cana-1621	120	21	lists	list	NOUN
cana-1621	120	22	into	into	ADP
cana-1621	120	23	one	one	NUM
cana-1621	120	24	consensus	consensus	NOUN
cana-1621	120	25	ranking	ranking	NOUN
cana-1621	120	26	.	.	PUNCT
cana-1621	121	1	these	these	DET
cana-1621	121	2	ranks	rank	NOUN
cana-1621	121	3	are	be	AUX
cana-1621	121	4	then	then	ADV
cana-1621	121	5	combined	combine	VERB
cana-1621	121	6	together	together	ADV
cana-1621	121	7	for	for	ADP
cana-1621	121	8	getting	get	VERB
cana-1621	121	9	the	the	DET
cana-1621	121	10	optimal	optimal	ADJ
cana-1621	121	11	result	result	NOUN
cana-1621	121	12	.	.	PUNCT
cana-1621	122	1	hybrid	hybrid	ADJ
cana-1621	122	2	feature	feature	NOUN
cana-1621	122	3	selection	selection	NOUN
cana-1621	122	4	with	with	ADP
cana-1621	122	5	ensemble	ensemble	ADJ
cana-1621	122	6	rank	rank	NOUN
cana-1621	122	7	aggregation	aggregation	NOUN
cana-1621	122	8	method	method	NOUN
cana-1621	122	9	is	be	AUX
cana-1621	122	10	implemented	implement	VERB
cana-1621	122	11	in	in	ADP
cana-1621	122	12	python	python	PROPN
cana-1621	122	13	.	.	PUNCT
cana-1621	123	1	before	before	ADP
cana-1621	123	2	applying	apply	VERB
cana-1621	123	3	feature	feature	NOUN
cana-1621	123	4	selection	selection	NOUN
cana-1621	123	5	and	and	CCONJ
cana-1621	123	6	rank	rank	NOUN
cana-1621	123	7	aggregation	aggregation	NOUN
cana-1621	123	8	algorithms	algorithm	NOUN
cana-1621	123	9	,	,	PUNCT
cana-1621	123	10	the	the	DET
cana-1621	123	11	random	random	ADJ
cana-1621	123	12	forest	forest	NOUN
cana-1621	123	13	classifier	classifier	NOUN
cana-1621	123	14	is	be	AUX
cana-1621	123	15	used	use	VERB
cana-1621	123	16	to	to	PART
cana-1621	123	17	classify	classify	VERB
cana-1621	123	18	data	datum	NOUN
cana-1621	123	19	set	set	VERB
cana-1621	123	20	and	and	CCONJ
cana-1621	123	21	the	the	DET
cana-1621	123	22	accuracy	accuracy	NOUN
cana-1621	123	23	obtained	obtain	VERB
cana-1621	123	24	for	for	ADP
cana-1621	123	25	australian	australian	ADJ
cana-1621	123	26	and	and	CCONJ
cana-1621	123	27	german	german	ADJ
cana-1621	123	28	data	datum	NOUN
cana-1621	123	29	sets	set	NOUN
cana-1621	123	30	are	be	AUX
cana-1621	123	31	0.85	0.85	NUM
cana-1621	123	32	and	and	CCONJ
cana-1621	123	33	0.75	0.75	NUM
cana-1621	123	34	respectively	respectively	ADV
cana-1621	123	35	.	.	PUNCT
cana-1621	124	1	fig1	fig1	PROPN
cana-1621	124	2	.	.	PUNCT
cana-1621	125	1	accuracy	accuracy	NOUN
cana-1621	125	2	foraustralian	foraustralian	ADJ
cana-1621	125	3	dataset	dataset	NOUN
cana-1621	125	4	fig2	fig2	PROPN
cana-1621	125	5	.	.	PUNCT
cana-1621	126	1	accuracy	accuracy	NOUN
cana-1621	126	2	for	for	ADP
cana-1621	126	3	german	german	ADJ
cana-1621	126	4	dataset	dataset	NOUN
cana-1621	126	5	table1	table1	PROPN
cana-1621	126	6	shows	show	VERB
cana-1621	126	7	the	the	DET
cana-1621	126	8	accuracy	accuracy	NOUN
cana-1621	126	9	obtained	obtain	VERB
cana-1621	126	10	before	before	ADP
cana-1621	126	11	applying	apply	VERB
cana-1621	126	12	different	different	ADJ
cana-1621	126	13	rank	rank	NOUN
cana-1621	126	14	aggregation	aggregation	NOUN
cana-1621	126	15	methods	method	NOUN
cana-1621	126	16	.	.	PUNCT
cana-1621	127	1	in	in	ADP
cana-1621	127	2	this	this	DET
cana-1621	127	3	study	study	NOUN
cana-1621	127	4	we	we	PRON
cana-1621	127	5	used	use	VERB
cana-1621	127	6	the	the	DET
cana-1621	127	7	random	random	ADJ
cana-1621	127	8	classifier	classifier	NOUN
cana-1621	127	9	for	for	ADP
cana-1621	127	10	classification	classification	NOUN
cana-1621	127	11	.	.	PUNCT
cana-1621	128	1	the	the	DET
cana-1621	128	2	fisher	fisher	PROPN
cana-1621	128	3	score	score	NOUN
cana-1621	128	4	feature	feature	NOUN
cana-1621	128	5	selection	selection	NOUN
cana-1621	128	6	produced	produce	VERB
cana-1621	128	7	highest	high	ADJ
cana-1621	128	8	accuracy	accuracy	NOUN
cana-1621	128	9	in	in	ADP
cana-1621	128	10	australian	australian	ADJ
cana-1621	128	11	data	datum	NOUN
cana-1621	128	12	set	set	VERB
cana-1621	128	13	and	and	CCONJ
cana-1621	128	14	chi	chi	ADJ
cana-1621	128	15	-	-	PUNCT
cana-1621	128	16	square	square	NOUN
cana-1621	128	17	produced	produce	VERB
cana-1621	128	18	highest	high	ADJ
cana-1621	128	19	accuracy	accuracy	NOUN
cana-1621	128	20	for	for	ADP
cana-1621	128	21	german	german	ADJ
cana-1621	128	22	data	datum	NOUN
cana-1621	128	23	set	set	VERB
cana-1621	128	24	.	.	PUNCT
cana-1621	129	1	australian	australian	ADJ
cana-1621	129	2	credit	credit	NOUN
cana-1621	129	3	data	datum	NOUN
cana-1621	129	4	set	set	VERB
cana-1621	129	5	german	german	ADJ
cana-1621	129	6	credit	credit	NOUN
cana-1621	129	7	data	datum	NOUN
cana-1621	129	8	set	set	VERB
cana-1621	129	9	feature	feature	NOUN
cana-1621	129	10	selection	selection	NOUN
cana-1621	129	11	techniques	technique	NOUN
cana-1621	129	12	accuracy	accuracy	NOUN
cana-1621	129	13	precision	precision	NOUN
cana-1621	129	14	recall	recall	PROPN
cana-1621	129	15	accuracy	accuracy	PROPN
cana-1621	129	16	precision	precision	NOUN
cana-1621	129	17	recall	recall	VERB
cana-1621	129	18	chi	chi	PROPN
cana-1621	129	19	-	-	PUNCT
cana-1621	129	20	square	square	ADJ
cana-1621	129	21	0.869	0.869	NUM
cana-1621	129	22	0.85	0.85	NUM
cana-1621	129	23	0.981	0.981	NUM
cana-1621	129	24	0.785	0.785	NUM
cana-1621	129	25	0.806	0.806	NUM
cana-1621	129	26	0.9148	0.9148	NUM
cana-1621	129	27	fisherscore	fisherscore	VERB
cana-1621	129	28	0.884	0.884	NUM
cana-1621	129	29	0.862	0.862	NUM
cana-1621	129	30	0.932	0.932	NUM
cana-1621	129	31	0.74	0.74	NUM
cana-1621	129	32	0.743	0.743	NUM
cana-1621	129	33	0.964	0.964	NUM
cana-1621	129	34	boruta	boruta	PROPN
cana-1621	129	35	0.862	0.862	NUM
cana-1621	129	36	0.829	0.829	NUM
cana-1621	129	37	0.918	0.918	NUM
cana-1621	129	38	0.78	0.78	NUM
cana-1621	129	39	0.7486	0.7486	NUM
cana-1621	129	40	0.971	0.971	NUM
cana-1621	129	41	informationgain	informationgain	VERB
cana-1621	129	42	0.869	0.869	NUM
cana-1621	129	43	0.841	0.841	NUM
cana-1621	129	44	0.932	0.932	NUM
cana-1621	129	45	0.76	0.76	NUM
cana-1621	129	46	0.7	0.7	NUM
cana-1621	129	47	0.9	0.9	NUM
cana-1621	129	48	table	table	NOUN
cana-1621	129	49	1	1	NUM
cana-1621	129	50	.	.	PUNCT
cana-1621	129	51	acuuracy	acuuracy	NOUN
cana-1621	129	52	obtained	obtain	VERB
cana-1621	129	53	after	after	ADP
cana-1621	129	54	applying	apply	VERB
cana-1621	129	55	different	different	ADJ
cana-1621	129	56	feature	feature	NOUN
cana-1621	129	57	selection	selection	NOUN
cana-1621	129	58	techniques	technique	NOUN
cana-1621	129	59	table2	table2	NOUN
cana-1621	129	60	shows	show	VERB
cana-1621	129	61	the	the	DET
cana-1621	129	62	accuracy	accuracy	NOUN
cana-1621	129	63	obtained	obtain	VERB
cana-1621	129	64	from	from	ADP
cana-1621	129	65	ensemble	ensemble	ADJ
cana-1621	129	66	feature	feature	NOUN
cana-1621	129	67	selection	selection	NOUN
cana-1621	129	68	using	use	VERB
cana-1621	129	69	rank	rank	NOUN
cana-1621	129	70	aggregartion	aggregartion	NOUN
cana-1621	129	71	.	.	PUNCT
cana-1621	130	1	the	the	DET
cana-1621	130	2	rank	rank	NOUN
cana-1621	130	3	obtained	obtain	VERB
cana-1621	130	4	from	from	ADP
cana-1621	130	5	chi	chi	ADJ
cana-1621	130	6	-	-	PUNCT
cana-1621	130	7	square	square	ADJ
cana-1621	130	8	,	,	PUNCT
cana-1621	130	9	fisher	fisher	PROPN
cana-1621	130	10	score	score	NOUN
cana-1621	130	11	,	,	PUNCT
cana-1621	130	12	boruta	boruta	NOUN
cana-1621	130	13	and	and	CCONJ
cana-1621	130	14	informationgain	informationgain	NOUN
cana-1621	130	15	are	be	AUX
cana-1621	130	16	combined	combine	VERB
cana-1621	130	17	using	use	VERB
cana-1621	130	18	rank	rank	PROPN
cana-1621	130	19	aggraltion	aggraltion	PROPN
cana-1621	130	20	mc4	mc4	PROPN
cana-1621	130	21	,	,	PUNCT
cana-1621	130	22	borda	borda	NOUN
cana-1621	130	23	count	count	NOUN
cana-1621	130	24	and	and	CCONJ
cana-1621	130	25	random	random	ADJ
cana-1621	130	26	dictator	dictator	NOUN
cana-1621	130	27	.	.	PUNCT
cana-1621	131	1	communications	communication	NOUN
cana-1621	131	2	on	on	ADP
cana-1621	131	3	applied	apply	VERB
cana-1621	131	4	nonlinear	nonlinear	ADJ
cana-1621	131	5	analysis	analysis	NOUN
cana-1621	131	6	issn	issn	NOUN
cana-1621	131	7	:	:	PUNCT
cana-1621	131	8	1074	1074	NUM
cana-1621	131	9	-	-	PUNCT
cana-1621	131	10	133x	133x	NUM
cana-1621	131	11	vol	vol	NOUN
cana-1621	131	12	32	32	NUM
cana-1621	131	13	no	no	NOUN
cana-1621	131	14	.	.	NOUN
cana-1621	131	15	1	1	NUM
cana-1621	131	16	(	(	PUNCT
cana-1621	131	17	2025	2025	NUM
cana-1621	131	18	)	)	PUNCT
cana-1621	131	19	69	69	NUM
cana-1621	132	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-1621	132	2	australian	australian	ADJ
cana-1621	132	3	credit	credit	NOUN
cana-1621	132	4	data	datum	NOUN
cana-1621	132	5	set	set	VERB
cana-1621	132	6	german	german	ADJ
cana-1621	132	7	credit	credit	NOUN
cana-1621	132	8	data	datum	NOUN
cana-1621	132	9	set	set	VERB
cana-1621	132	10	rank	rank	NOUN
cana-1621	132	11	aggregation	aggregation	NOUN
cana-1621	132	12	methods	method	NOUN
cana-1621	132	13	accuracy	accuracy	NOUN
cana-1621	132	14	precision	precision	NOUN
cana-1621	132	15	recall	recall	PROPN
cana-1621	132	16	accuracy	accuracy	PROPN
cana-1621	132	17	precision	precision	NOUN
cana-1621	132	18	recall	recall	VERB
cana-1621	132	19	mc4	mc4	PROPN
cana-1621	132	20	0.913	0.913	NUM
cana-1621	132	21	0.9078	0.9078	NUM
cana-1621	132	22	0.9324	0.9324	NUM
cana-1621	132	23	0.775	0.775	NUM
cana-1621	132	24	0.8	0.8	NUM
cana-1621	132	25	0.96	0.96	NUM
cana-1621	132	26	borda	borda	NOUN
cana-1621	132	27	count	count	NOUN
cana-1621	132	28	0.88	0.88	NUM
cana-1621	132	29	0.871	0.871	NUM
cana-1621	132	30	0.918	0.918	NUM
cana-1621	132	31	0.77	0.77	NUM
cana-1621	132	32	0.8	0.8	NUM
cana-1621	132	33	0.9	0.9	NUM
cana-1621	132	34	random	random	ADJ
cana-1621	132	35	dictator	dictator	NOUN
cana-1621	132	36	0.89	0.89	NUM
cana-1621	132	37	0.86	0.86	NUM
cana-1621	132	38	0.92	0.92	NUM
cana-1621	132	39	0.76	0.76	NUM
cana-1621	132	40	0.8	0.8	NUM
cana-1621	132	41	0.95	0.95	NUM
cana-1621	132	42	table	table	NOUN
cana-1621	132	43	2	2	NUM
cana-1621	132	44	.	.	PUNCT
cana-1621	132	45	acuuracy	acuuracy	NOUN
cana-1621	132	46	obtained	obtain	VERB
cana-1621	132	47	after	after	ADP
cana-1621	132	48	applying	apply	VERB
cana-1621	132	49	different	different	ADJ
cana-1621	132	50	rank	rank	NOUN
cana-1621	132	51	aggregation	aggregation	NOUN
cana-1621	132	52	method	method	NOUN
cana-1621	132	53	the	the	DET
cana-1621	132	54	aggregate	aggregate	ADJ
cana-1621	132	55	rank	rank	NOUN
cana-1621	132	56	obtained	obtain	VERB
cana-1621	132	57	from	from	ADP
cana-1621	132	58	mc4	mc4	PROPN
cana-1621	132	59	,	,	PUNCT
cana-1621	132	60	borda	borda	NOUN
cana-1621	132	61	and	and	CCONJ
cana-1621	132	62	random	random	ADJ
cana-1621	132	63	dictator	dictator	NOUN
cana-1621	132	64	are	be	AUX
cana-1621	132	65	presented	present	VERB
cana-1621	132	66	in	in	ADP
cana-1621	132	67	table	table	NOUN
cana-1621	132	68	3	3	NUM
cana-1621	132	69	and	and	CCONJ
cana-1621	132	70	table4	table4	PROPN
cana-1621	132	71	.	.	PUNCT
cana-1621	133	1	table	table	NOUN
cana-1621	133	2	3	3	NUM
cana-1621	133	3	show	show	VERB
cana-1621	133	4	the	the	DET
cana-1621	133	5	result	result	NOUN
cana-1621	133	6	obtained	obtain	VERB
cana-1621	133	7	from	from	ADP
cana-1621	133	8	australian	australian	ADJ
cana-1621	133	9	data	datum	NOUN
cana-1621	133	10	set	set	VERB
cana-1621	133	11	and	and	CCONJ
cana-1621	133	12	table	table	NOUN
cana-1621	133	13	4	4	NUM
cana-1621	133	14	shows	show	VERB
cana-1621	133	15	the	the	DET
cana-1621	133	16	result	result	NOUN
cana-1621	133	17	achieved	achieve	VERB
cana-1621	133	18	from	from	ADP
cana-1621	133	19	german	german	ADJ
cana-1621	133	20	data	datum	NOUN
cana-1621	133	21	set	set	VERB
cana-1621	133	22	.	.	PUNCT
cana-1621	134	1	borda	borda	PROPN
cana-1621	134	2	mc4	mc4	PROPN
cana-1621	134	3	random	random	ADJ
cana-1621	134	4	dictator	dictator	NOUN
cana-1621	134	5	a8	a8	PROPN
cana-1621	134	6	12.250	12.250	NUM
cana-1621	134	7	a13	a13	PROPN
cana-1621	134	8	10.500	10.500	NUM
cana-1621	134	9	a14	a14	PROPN
cana-1621	134	10	9.750	9.750	NUM
cana-1621	134	11	a5	a5	NOUN
cana-1621	134	12	9.500	9.500	NUM
cana-1621	134	13	a10	a10	NUM
cana-1621	134	14	9.125	9.125	NUM
cana-1621	134	15	a3	a3	NOUN
cana-1621	134	16	8.000	8.000	NUM
cana-1621	134	17	a9	a9	NOUN
cana-1621	134	18	7.625	7.625	NUM
cana-1621	134	19	a7	a7	PROPN
cana-1621	134	20	7.000	7.000	NUM
cana-1621	134	21	a2	a2	PROPN
cana-1621	134	22	6.500	6.500	NUM
cana-1621	134	23	a4	a4	NOUN
cana-1621	134	24	5.750	5.750	NUM
cana-1621	134	25	a12	a12	NOUN
cana-1621	134	26	5.750	5.750	NUM
cana-1621	134	27	a6	a6	NOUN
cana-1621	134	28	5.000	5.000	NUM
cana-1621	134	29	a11	a11	NOUN
cana-1621	134	30	4.250	4.250	NUM
cana-1621	134	31	a1	a1	NOUN
cana-1621	134	32	4.000	4.000	NUM
cana-1621	134	33	a1	a1	NOUN
cana-1621	134	34	13	13	NUM
cana-1621	134	35	a2	a2	PROPN
cana-1621	134	36	9	9	NUM
cana-1621	134	37	a3	a3	NOUN
cana-1621	134	38	6	6	NUM
cana-1621	134	39	a4	a4	NOUN
cana-1621	134	40	11	11	NUM
cana-1621	134	41	a5	a5	NOUN
cana-1621	134	42	4	4	NUM
cana-1621	134	43	a6	a6	NOUN
cana-1621	134	44	12	12	NUM
cana-1621	134	45	a7	a7	PROPN
cana-1621	134	46	8	8	NUM
cana-1621	134	47	a8	a8	PROPN
cana-1621	134	48	1	1	NUM
cana-1621	134	49	a9	a9	PROPN
cana-1621	134	50	7	7	NUM
cana-1621	134	51	a10	a10	NOUN
cana-1621	134	52	5	5	NUM
cana-1621	134	53	a11	a11	PROPN
cana-1621	134	54	14	14	NUM
cana-1621	134	55	a12	a12	NOUN
cana-1621	134	56	10	10	NUM
cana-1621	134	57	a1	a1	PROPN
cana-1621	134	58	13.206910	13.206910	NUM
cana-1621	134	59	a2	a2	PROPN
cana-1621	134	60	9.561778	9.561778	NUM
cana-1621	134	61	a3	a3	NOUN
cana-1621	134	62	2.289081	2.289081	NUM
cana-1621	134	63	a4	a4	NOUN
cana-1621	134	64	9.689620	9.689620	NUM
cana-1621	134	65	a5	a5	NOUN
cana-1621	134	66	1.935323	1.935323	NUM
cana-1621	134	67	a6	a6	NOUN
cana-1621	134	68	12.479884	12.479884	NUM
cana-1621	134	69	a7	a7	PROPN
cana-1621	134	70	11.806383	11.806383	NUM
cana-1621	134	71	a8	a8	PROPN
cana-1621	134	72	1.053010	1.053010	NUM
cana-1621	134	73	a9	a9	NOUN
cana-1621	134	74	5.953927	5.953927	NUM
cana-1621	134	75	a10	a10	NOUN
cana-1621	134	76	4.890913	4.890913	NUM
cana-1621	134	77	a11	a11	PROPN
cana-1621	134	78	13.382848	13.382848	NUM
cana-1621	134	79	a12	a12	PROPN
cana-1621	134	80	11.493168	11.493168	NUM
cana-1621	134	81	a13	a13	PROPN
cana-1621	134	82	1.758553	1.758553	NUM
cana-1621	134	83	a14	a14	NOUN
cana-1621	134	84	1.336530	1.336530	NUM
cana-1621	134	85	table	table	NOUN
cana-1621	134	86	3	3	NUM
cana-1621	134	87	.	.	PUNCT
cana-1621	134	88	aggregate	aggregate	ADJ
cana-1621	134	89	rank	rank	PROPN
cana-1621	134	90	obtained	obtain	VERB
cana-1621	134	91	from	from	ADP
cana-1621	134	92	australian	australian	ADJ
cana-1621	134	93	data	datum	NOUN
cana-1621	134	94	set	set	VERB
cana-1621	134	95	borda	borda	NOUN
cana-1621	134	96	mc4	mc4	PROPN
cana-1621	134	97	random	random	ADJ
cana-1621	134	98	dictator	dictator	NOUN
cana-1621	134	99	a1	a1	PROPN
cana-1621	134	100	15.875	15.875	NUM
cana-1621	134	101	a3	a3	NOUN
cana-1621	134	102	15.625	15.625	NUM
cana-1621	134	103	a2	a2	PROPN
cana-1621	134	104	13.375	13.375	NUM
cana-1621	134	105	a10	a10	NOUN
cana-1621	134	106	11.750	11.750	NUM
cana-1621	134	107	a7	a7	PROPN
cana-1621	134	108	11.375	11.375	NUM
cana-1621	134	109	a15	a15	NOUN
cana-1621	134	110	11.250	11.250	NUM
cana-1621	134	111	a9	a9	NOUN
cana-1621	134	112	11.000	11.000	NUM
cana-1621	134	113	a4	a4	NUM
cana-1621	134	114	10.750	10.750	NUM
cana-1621	134	115	a19	a19	PROPN
cana-1621	134	116	10.500	10.500	NUM
cana-1621	134	117	a20	a20	NOUN
cana-1621	134	118	10.250	10.250	NUM
cana-1621	134	119	a6	a6	NOUN
cana-1621	134	120	10.125	10.125	NUM
cana-1621	134	121	a1	a1	NOUN
cana-1621	134	122	:	:	PUNCT
cana-1621	134	123	1	1	NUM
cana-1621	134	124	a2	a2	PROPN
cana-1621	134	125	:	:	PUNCT
cana-1621	134	126	3	3	NUM
cana-1621	134	127	a3	a3	NOUN
cana-1621	134	128	:	:	PUNCT
cana-1621	134	129	2	2	NUM
cana-1621	134	130	a4	a4	NOUN
cana-1621	134	131	:	:	PUNCT
cana-1621	134	132	8	8	NUM
cana-1621	134	133	a5	a5	NOUN
cana-1621	134	134	:	:	PUNCT
cana-1621	134	135	9	9	NUM
cana-1621	134	136	a6	a6	NOUN
cana-1621	134	137	:	:	PUNCT
cana-1621	134	138	11	11	NUM
cana-1621	134	139	a7	a7	NOUN
cana-1621	134	140	:	:	PUNCT
cana-1621	134	141	8	8	NUM
cana-1621	134	142	a8	a8	NOUN
cana-1621	134	143	:	:	PUNCT
cana-1621	134	144	12	12	NUM
cana-1621	134	145	a9	a9	NOUN
cana-1621	134	146	:	:	PUNCT
cana-1621	134	147	7	7	NUM
cana-1621	134	148	a10	a10	NOUN
cana-1621	134	149	:	:	PUNCT
cana-1621	134	150	4	4	NUM
cana-1621	134	151	a11	a11	NOUN
cana-1621	134	152	:	:	PUNCT
cana-1621	134	153	14	14	NUM
cana-1621	134	154	a1	a1	NOUN
cana-1621	134	155	4.034462	4.034462	NUM
cana-1621	134	156	a2	a2	PROPN
cana-1621	134	157	7.420083	7.420083	NUM
cana-1621	134	158	a3	a3	NOUN
cana-1621	134	159	5.440116	5.440116	NUM
cana-1621	134	160	a4	a4	NOUN
cana-1621	134	161	8.287495	8.287495	NUM
cana-1621	134	162	a5	a5	NOUN
cana-1621	134	163	8.193554	8.193554	NUM
cana-1621	134	164	a6	a6	NOUN
cana-1621	134	165	11.368984	11.368984	NUM
cana-1621	135	1	a7	a7	PROPN
cana-1621	135	2	8.525176	8.525176	NUM
cana-1621	135	3	a8	a8	PROPN
cana-1621	135	4	13.154061	13.154061	NUM
cana-1621	135	5	a9	a9	PROPN
cana-1621	135	6	9.430118	9.430118	NUM
cana-1621	135	7	a10	a10	NOUN
cana-1621	135	8	9.287205	9.287205	NUM
cana-1621	135	9	a11	a11	PROPN
cana-1621	135	10	16.392611	16.392611	NUM
cana-1621	135	11	communications	communication	NOUN
cana-1621	135	12	on	on	ADP
cana-1621	135	13	applied	apply	VERB
cana-1621	135	14	nonlinear	nonlinear	ADJ
cana-1621	135	15	analysis	analysis	NOUN
cana-1621	135	16	issn	issn	NOUN
cana-1621	135	17	:	:	PUNCT
cana-1621	135	18	1074	1074	NUM
cana-1621	135	19	-	-	PUNCT
cana-1621	135	20	133x	133x	NUM
cana-1621	135	21	vol	vol	NOUN
cana-1621	135	22	32	32	NUM
cana-1621	135	23	no	no	NOUN
cana-1621	135	24	.	.	NOUN
cana-1621	135	25	1	1	NUM
cana-1621	135	26	(	(	PUNCT
cana-1621	135	27	2025	2025	NUM
cana-1621	135	28	)	)	PUNCT
cana-1621	135	29	70	70	NUM
cana-1621	135	30	https://internationalpubls.com	https://internationalpubls.com	X
cana-1621	135	31	a5	a5	PROPN
cana-1621	135	32	10.125	10.125	NUM
cana-1621	135	33	a8	a8	PROPN
cana-1621	135	34	9.750	9.750	NUM
cana-1621	135	35	a12	a12	NOUN
cana-1621	135	36	9.250	9.250	NUM
cana-1621	135	37	a11	a11	PROPN
cana-1621	135	38	8.750	8.750	NUM
cana-1621	135	39	a16	a16	PROPN
cana-1621	135	40	8.500	8.500	NUM
cana-1621	135	41	a18	a18	NOUN
cana-1621	135	42	8.500	8.500	NUM
cana-1621	135	43	a14	a14	PROPN
cana-1621	135	44	8.125	8.125	NUM
cana-1621	135	45	a13	a13	NOUN
cana-1621	135	46	7.625	7.625	NUM
cana-1621	135	47	a17	a17	NOUN
cana-1621	135	48	7.500	7.500	NUM
cana-1621	135	49	a12	a12	NOUN
cana-1621	135	50	:	:	PUNCT
cana-1621	135	51	13	13	NUM
cana-1621	135	52	a13	a13	NOUN
cana-1621	135	53	:	:	PUNCT
cana-1621	135	54	17	17	NUM
cana-1621	135	55	a14	a14	NOUN
cana-1621	135	56	:	:	PUNCT
cana-1621	135	57	18	18	NUM
cana-1621	135	58	a15	a15	NOUN
cana-1621	135	59	:	:	PUNCT
cana-1621	135	60	5	5	NUM
cana-1621	135	61	a16	a16	NOUN
cana-1621	135	62	:	:	PUNCT
cana-1621	135	63	16	16	NUM
cana-1621	135	64	a17	a17	NOUN
cana-1621	135	65	:	:	PUNCT
cana-1621	135	66	19	19	NUM
cana-1621	135	67	a18	a18	NOUN
cana-1621	135	68	:	:	PUNCT
cana-1621	135	69	15	15	NUM
cana-1621	135	70	a19	a19	NOUN
cana-1621	135	71	:	:	PUNCT
cana-1621	135	72	10	10	NUM
cana-1621	135	73	a20	a20	NOUN
cana-1621	135	74	:	:	PUNCT
cana-1621	135	75	6	6	NUM
cana-1621	135	76	a12	a12	NOUN
cana-1621	135	77	12.654030	12.654030	NUM
cana-1621	135	78	a13	a13	PROPN
cana-1621	135	79	13.910496	13.910496	NUM
cana-1621	135	80	a14	a14	PROPN
cana-1621	135	81	15.199035	15.199035	NUM
cana-1621	135	82	a15	a15	NOUN
cana-1621	135	83	10.566045	10.566045	NUM
cana-1621	135	84	a16	a16	PROPN
cana-1621	135	85	18.450728	18.450728	NUM
cana-1621	135	86	a17	a17	PROPN
cana-1621	135	87	17.759871	17.759871	NUM
cana-1621	135	88	a18	a18	PROPN
cana-1621	135	89	18.537267	18.537267	PROPN
cana-1621	135	90	a19	a19	PROPN
cana-1621	135	91	11.135816	11.135816	NUM
cana-1621	135	92	a20	a20	PROPN
cana-1621	135	93	12.101246	12.101246	NUM
cana-1621	135	94	table	table	NOUN
cana-1621	135	95	4	4	NUM
cana-1621	135	96	.	.	PUNCT
cana-1621	135	97	aggregate	aggregate	ADJ
cana-1621	135	98	rank	rank	PROPN
cana-1621	135	99	obtained	obtain	VERB
cana-1621	135	100	from	from	ADP
cana-1621	135	101	german	german	ADJ
cana-1621	135	102	data	datum	NOUN
cana-1621	135	103	set	set	VERB
cana-1621	135	104	table5	table5	NOUN
cana-1621	135	105	shows	show	VERB
cana-1621	135	106	the	the	DET
cana-1621	135	107	accuracy	accuracy	NOUN
cana-1621	135	108	obtained	obtain	VERB
cana-1621	135	109	from	from	ADP
cana-1621	135	110	hybrid	hybrid	ADJ
cana-1621	135	111	feature	feature	NOUN
cana-1621	135	112	selection	selection	NOUN
cana-1621	135	113	using	use	VERB
cana-1621	135	114	ensemble	ensemble	ADJ
cana-1621	135	115	rank	rank	NOUN
cana-1621	135	116	aggregartion	aggregartion	NOUN
cana-1621	135	117	.	.	PUNCT
cana-1621	136	1	the	the	DET
cana-1621	136	2	aggregate	aggregate	ADJ
cana-1621	136	3	rank	rank	NOUN
cana-1621	136	4	obtained	obtain	VERB
cana-1621	136	5	from	from	ADP
cana-1621	136	6	mc4	mc4	PROPN
cana-1621	136	7	,	,	PUNCT
cana-1621	136	8	borda	borda	NOUN
cana-1621	136	9	count	count	NOUN
cana-1621	136	10	and	and	CCONJ
cana-1621	136	11	random	random	ADJ
cana-1621	136	12	dictator	dictator	NOUN
cana-1621	136	13	are	be	AUX
cana-1621	136	14	combined	combine	VERB
cana-1621	136	15	together	together	ADV
cana-1621	136	16	for	for	ADP
cana-1621	136	17	getting	get	VERB
cana-1621	136	18	more	more	ADV
cana-1621	136	19	accurate	accurate	ADJ
cana-1621	136	20	result	result	NOUN
cana-1621	136	21	.	.	PUNCT
cana-1621	137	1	the	the	DET
cana-1621	137	2	result	result	NOUN
cana-1621	137	3	shows	show	VERB
cana-1621	137	4	that	that	SCONJ
cana-1621	137	5	ensemble	ensemble	ADJ
cana-1621	137	6	rank	rank	NOUN
cana-1621	137	7	aggregation	aggregation	NOUN
cana-1621	137	8	provided	provide	VERB
cana-1621	137	9	more	more	ADJ
cana-1621	137	10	accuracy	accuracy	NOUN
cana-1621	137	11	and	and	CCONJ
cana-1621	137	12	the	the	DET
cana-1621	137	13	fig.3	fig.3	PROPN
cana-1621	137	14	and	and	CCONJ
cana-1621	137	15	fig.4	fig.4	PROPN
cana-1621	137	16	shows	show	NOUN
cana-1621	137	17	the	the	DET
cana-1621	137	18	result	result	NOUN
cana-1621	137	19	obtained	obtain	VERB
cana-1621	137	20	from	from	ADP
cana-1621	137	21	australian	australian	ADJ
cana-1621	137	22	and	and	CCONJ
cana-1621	137	23	german	german	ADJ
cana-1621	137	24	data	datum	NOUN
cana-1621	137	25	sets	set	NOUN
cana-1621	137	26	.	.	PUNCT
cana-1621	138	1	data	datum	NOUN
cana-1621	138	2	set	set	VERB
cana-1621	138	3	accuracy	accuracy	NOUN
cana-1621	138	4	precision	precision	NOUN
cana-1621	138	5	recall	recall	VERB
cana-1621	138	6	australian	australian	ADJ
cana-1621	138	7	data	datum	NOUN
cana-1621	138	8	set	set	VERB
cana-1621	138	9	0.913	0.913	NUM
cana-1621	138	10	0.9078	0.9078	NUM
cana-1621	138	11	0.9324	0.9324	NUM
cana-1621	138	12	german	german	ADJ
cana-1621	138	13	data	datum	NOUN
cana-1621	138	14	set	set	VERB
cana-1621	138	15	0.901	0.901	NUM
cana-1621	138	16	0.9	0.9	NUM
cana-1621	138	17	0.96	0.96	NUM
cana-1621	138	18	table5	table5	NOUN
cana-1621	138	19	shows	show	VERB
cana-1621	138	20	the	the	DET
cana-1621	138	21	accuracy	accuracy	NOUN
cana-1621	138	22	obtained	obtain	VERB
cana-1621	138	23	from	from	ADP
cana-1621	138	24	hybrid	hybrid	ADJ
cana-1621	138	25	feature	feature	NOUN
cana-1621	138	26	selection	selection	NOUN
cana-1621	138	27	5	5	NUM
cana-1621	138	28	.	.	PUNCT
cana-1621	138	29	conclusion	conclusion	NOUN
cana-1621	138	30	this	this	DET
cana-1621	138	31	paper	paper	NOUN
cana-1621	138	32	we	we	PRON
cana-1621	138	33	focus	focus	VERB
cana-1621	138	34	on	on	ADP
cana-1621	138	35	hybrid	hybrid	ADJ
cana-1621	138	36	feature	feature	NOUN
cana-1621	138	37	selection	selection	NOUN
cana-1621	138	38	through	through	ADP
cana-1621	138	39	ensemble	ensemble	ADJ
cana-1621	138	40	rank	rank	NOUN
cana-1621	138	41	aggregation	aggregation	NOUN
cana-1621	138	42	.	.	PUNCT
cana-1621	139	1	in	in	ADP
cana-1621	139	2	this	this	DET
cana-1621	139	3	study	study	NOUN
cana-1621	139	4	the	the	DET
cana-1621	139	5	rank	rank	NOUN
cana-1621	139	6	produced	produce	VERB
cana-1621	139	7	by	by	ADP
cana-1621	139	8	fishers	fisher	NOUN
cana-1621	139	9	score	score	NOUN
cana-1621	139	10	,	,	PUNCT
cana-1621	139	11	information	information	NOUN
cana-1621	139	12	gain	gain	NOUN
cana-1621	139	13	,	,	PUNCT
cana-1621	139	14	chi	chi	PROPN
cana-1621	139	15	square	square	PROPN
cana-1621	139	16	and	and	CCONJ
cana-1621	139	17	brouta	brouta	ADV
cana-1621	139	18	are	be	AUX
cana-1621	139	19	combined	combine	VERB
cana-1621	139	20	using	use	VERB
cana-1621	139	21	different	different	ADJ
cana-1621	139	22	rank	rank	NOUN
cana-1621	139	23	aggregation	aggregation	NOUN
cana-1621	139	24	method	method	PROPN
cana-1621	139	25	mc4	mc4	PROPN
cana-1621	139	26	,	,	PUNCT
cana-1621	139	27	borda	borda	NOUN
cana-1621	139	28	and	and	CCONJ
cana-1621	139	29	random	random	ADJ
cana-1621	139	30	dictator	dictator	NOUN
cana-1621	139	31	.	.	PUNCT
cana-1621	140	1	the	the	DET
cana-1621	140	2	optimum	optimum	ADJ
cana-1621	140	3	rank	rank	NOUN
cana-1621	140	4	for	for	ADP
cana-1621	140	5	each	each	DET
cana-1621	140	6	attribute	attribute	NOUN
cana-1621	140	7	is	be	AUX
cana-1621	140	8	calculated	calculate	VERB
cana-1621	140	9	by	by	ADP
cana-1621	140	10	combing	comb	VERB
cana-1621	140	11	the	the	DET
cana-1621	140	12	result	result	NOUN
cana-1621	140	13	obtained	obtain	VERB
cana-1621	140	14	from	from	ADP
cana-1621	140	15	mc4	mc4	PROPN
cana-1621	140	16	,	,	PUNCT
cana-1621	140	17	borda	borda	NOUN
cana-1621	140	18	and	and	CCONJ
cana-1621	140	19	random	random	ADJ
cana-1621	140	20	dictator	dictator	NOUN
cana-1621	140	21	.	.	PUNCT
cana-1621	141	1	finally	finally	ADV
cana-1621	141	2	the	the	DET
cana-1621	141	3	wrapper	wrapper	NOUN
cana-1621	141	4	method	method	NOUN
cana-1621	141	5	is	be	AUX
cana-1621	141	6	applied	apply	VERB
cana-1621	141	7	for	for	ADP
cana-1621	141	8	feature	feature	NOUN
cana-1621	141	9	subset	subset	NOUN
cana-1621	141	10	selection	selection	NOUN
cana-1621	141	11	.	.	PUNCT
cana-1621	142	1	the	the	DET
cana-1621	142	2	results	result	NOUN
cana-1621	142	3	shows	show	VERB
cana-1621	142	4	that	that	SCONJ
cana-1621	142	5	hybrid	hybrid	ADJ
cana-1621	142	6	feature	feature	NOUN
cana-1621	142	7	selection	selection	NOUN
cana-1621	142	8	through	through	ADP
cana-1621	142	9	ensemble	ensemble	ADJ
cana-1621	142	10	rank	rank	NOUN
cana-1621	142	11	aggregation	aggregation	NOUN
cana-1621	142	12	can	can	AUX
cana-1621	142	13	perform	perform	VERB
cana-1621	142	14	better	well	ADJ
cana-1621	142	15	than	than	ADP
cana-1621	142	16	individual	individual	ADJ
cana-1621	142	17	rank	rank	NOUN
cana-1621	142	18	aggregation	aggregation	NOUN
cana-1621	142	19	method	method	NOUN
cana-1621	142	20	.	.	PUNCT
cana-1621	143	1	in	in	ADP
cana-1621	143	2	this	this	DET
cana-1621	143	3	study	study	NOUN
cana-1621	143	4	we	we	PRON
cana-1621	143	5	used	use	VERB
cana-1621	143	6	only	only	ADV
cana-1621	143	7	one	one	NUM
cana-1621	143	8	classification	classification	NOUN
cana-1621	143	9	algorithm	algorithm	NOUN
cana-1621	143	10	but	but	CCONJ
cana-1621	143	11	in	in	ADP
cana-1621	143	12	future	future	NOUN
cana-1621	143	13	,	,	PUNCT
cana-1621	143	14	this	this	DET
cana-1621	143	15	model	model	NOUN
cana-1621	143	16	needs	need	VERB
cana-1621	143	17	to	to	PART
cana-1621	143	18	test	test	VERB
cana-1621	143	19	by	by	ADP
cana-1621	143	20	using	use	VERB
cana-1621	143	21	some	some	DET
cana-1621	143	22	more	more	ADJ
cana-1621	143	23	classification	classification	NOUN
cana-1621	143	24	algorithms	algorithm	NOUN
cana-1621	143	25	.	.	PUNCT
cana-1621	144	1	references	reference	NOUN
cana-1621	144	2	[	[	X
cana-1621	144	3	1	1	NUM
cana-1621	144	4	]	]	X
cana-1621	144	5	brownlee	brownlee	PROPN
cana-1621	144	6	,	,	PUNCT
cana-1621	144	7	j.	j.	PROPN
cana-1621	144	8	,2014.machine	,2014.machine	PUNCT
cana-1621	144	9	learning	learn	VERB
cana-1621	144	10	mastery	mastery	NOUN
cana-1621	144	11	.	.	PUNCT
cana-1621	145	1	[	[	X
cana-1621	145	2	online	online	X
cana-1621	145	3	]	]	X
cana-1621	145	4	available	available	ADJ
cana-1621	145	5	at	at	ADP
cana-1621	145	6	:	:	PUNCT
cana-1621	145	7	https://machinelearningmastery.com/anintroduction-to-feature-election/	https://machinelearningmastery.com/anintroduction-to-feature-election/	PROPN
cana-1621	146	1	[	[	X
cana-1621	146	2	accessed	access	VERB
cana-1621	146	3	january	january	PROPN
cana-1621	146	4	2019	2019	NUM
cana-1621	146	5	]	]	PUNCT
cana-1621	146	6	.	.	PUNCT
cana-1621	147	1	[	[	X
cana-1621	147	2	2	2	X
cana-1621	147	3	]	]	PUNCT
cana-1621	147	4	h.	h.	PROPN
cana-1621	147	5	liu	liu	PROPN
cana-1621	147	6	,	,	PUNCT
cana-1621	147	7	h.	h.	PROPN
cana-1621	147	8	m.	m.	PROPN
cana-1621	147	9	(	(	PUNCT
cana-1621	147	10	2010	2010	NUM
cana-1621	147	11	)	)	PUNCT
cana-1621	147	12	.	.	PUNCT
cana-1621	148	1	feature	feature	NOUN
cana-1621	148	2	selection	selection	NOUN
cana-1621	148	3	:	:	PUNCT
cana-1621	148	4	an	an	DET
cana-1621	148	5	ever	ever	ADV
cana-1621	148	6	evolving	evolve	VERB
cana-1621	148	7	frontier	frontier	NOUN
cana-1621	148	8	in	in	ADP
cana-1621	148	9	data	datum	NOUN
cana-1621	148	10	mining	mining	NOUN
cana-1621	148	11	.	.	PUNCT
cana-1621	149	1	[	[	X
cana-1621	149	2	3	3	X
cana-1621	149	3	]	]	X
cana-1621	149	4	gayathri	gayathri	PROPN
cana-1621	149	5	nagarajan	nagarajan	PROPN
cana-1621	149	6	,	,	PUNCT
cana-1621	149	7	l.	l.	PROPN
cana-1621	149	8	d.	d.	PROPN
cana-1621	149	9	(	(	PUNCT
cana-1621	149	10	2021	2021	NUM
cana-1621	149	11	)	)	PUNCT
cana-1621	149	12	.	.	PUNCT
cana-1621	150	1	a	a	DET
cana-1621	150	2	hybrid	hybrid	ADJ
cana-1621	150	3	feature	feature	NOUN
cana-1621	150	4	selection	selection	NOUN
cana-1621	150	5	model	model	NOUN
cana-1621	150	6	based	base	VERB
cana-1621	150	7	on	on	ADP
cana-1621	150	8	improved	improved	ADJ
cana-1621	150	9	squirrel	squirrel	NOUN
cana-1621	150	10	search	search	NOUN
cana-1621	150	11	.	.	PUNCT
cana-1621	151	1	springer	springer	NOUN
cana-1621	151	2	.	.	PUNCT
cana-1621	152	1	[	[	X
cana-1621	152	2	4	4	NUM
cana-1621	152	3	]	]	X
cana-1621	152	4	rahi	rahi	NOUN
cana-1621	152	5	jain	jain	PROPN
cana-1621	152	6	,	,	PUNCT
cana-1621	152	7	w.	w.	PROPN
cana-1621	152	8	x.	x.	PROPN
cana-1621	152	9	(	(	PUNCT
cana-1621	152	10	2022	2022	NUM
cana-1621	152	11	)	)	PUNCT
cana-1621	152	12	.	.	PUNCT
cana-1621	153	1	hybrid	hybrid	ADJ
cana-1621	153	2	rank	rank	NOUN
cana-1621	153	3	aggregation	aggregation	NOUN
cana-1621	153	4	(	(	PUNCT
cana-1621	153	5	hra	hra	PROPN
cana-1621	153	6	):	):	PUNCT
cana-1621	153	7	a	a	DET
cana-1621	153	8	novel	novel	ADJ
cana-1621	153	9	rank	rank	NOUN
cana-1621	153	10	aggregation	aggregation	NOUN
cana-1621	153	11	method	method	NOUN
cana-1621	153	12	for	for	ADP
cana-1621	153	13	ensemble	ensemble	ADJ
cana-1621	153	14	-	-	PUNCT
cana-1621	153	15	based	base	VERB
cana-1621	153	16	feature	feature	NOUN
cana-1621	153	17	selection	selection	NOUN
cana-1621	153	18	.	.	PUNCT
cana-1621	154	1	retrieved	retrieve	VERB
cana-1621	154	2	from	from	ADP
cana-1621	154	3	www.biorxiv.org	www.biorxiv.org	ADJ
cana-1621	154	4	:	:	PUNCT
cana-1621	154	5	https://www.biorxiv.org/content/10.1101/2022.07.21.501057v1.full	https://www.biorxiv.org/content/10.1101/2022.07.21.501057v1.full	X
cana-1621	154	6	.	.	PUNCT
cana-1621	155	1	[	[	X
cana-1621	155	2	5	5	NUM
cana-1621	155	3	]	]	X
cana-1621	155	4	shashi	shashi	PROPN
cana-1621	155	5	dahiya	dahiya	PROPN
cana-1621	155	6	,	,	PUNCT
cana-1621	155	7	s.	s.	PROPN
cana-1621	155	8	h.	h.	PROPN
cana-1621	155	9	(	(	PUNCT
cana-1621	155	10	n.d	n.d	PROPN
cana-1621	155	11	.	.	PROPN
cana-1621	155	12	)	)	PUNCT
cana-1621	155	13	.	.	PUNCT
cana-1621	156	1	a	a	DET
cana-1621	156	2	rank	rank	NOUN
cana-1621	156	3	aggregation	aggregation	NOUN
cana-1621	156	4	algorithm	algorithm	NOUN
cana-1621	156	5	for	for	ADP
cana-1621	156	6	ensemble	ensemble	ADJ
cana-1621	156	7	of	of	ADP
cana-1621	156	8	multiple	multiple	ADJ
cana-1621	156	9	feature	feature	NOUN
cana-1621	156	10	selection	selection	NOUN
cana-1621	156	11	techniques	technique	NOUN
cana-1621	156	12	in	in	ADP
cana-1621	156	13	credit	credit	NOUN
cana-1621	156	14	risk	risk	NOUN
cana-1621	156	15	evaluation	evaluation	NOUN
cana-1621	156	16	.	.	PUNCT
cana-1621	157	1	(	(	PUNCT
cana-1621	157	2	ijarai	ijarai	NOUN
cana-1621	157	3	)	)	PUNCT
cana-1621	157	4	international	international	ADJ
cana-1621	157	5	journal	journal	NOUN
cana-1621	157	6	of	of	ADP
cana-1621	157	7	advanced	advanced	ADJ
cana-1621	157	8	research	research	NOUN
cana-1621	157	9	in	in	ADP
cana-1621	157	10	artificial	artificial	ADJ
cana-1621	157	11	intelligence	intelligence	NOUN
cana-1621	157	12	.	.	PUNCT
cana-1621	158	1	[	[	X
cana-1621	158	2	6	6	NUM
cana-1621	158	3	]	]	X
cana-1621	158	4	wanwan	wanwan	PROPN
cana-1621	158	5	zheng	zheng	PROPN
cana-1621	158	6	,	,	PUNCT
cana-1621	158	7	m.	m.	PROPN
cana-1621	158	8	j.	j.	PROPN
cana-1621	158	9	,	,	PUNCT
cana-1621	158	10	2018	2018	NUM
cana-1621	158	11	.	.	PUNCT
cana-1621	158	12	comparing	compare	VERB
cana-1621	158	13	feature	feature	NOUN
cana-1621	158	14	selection	selection	NOUN
cana-1621	158	15	methods	method	NOUN
cana-1621	158	16	by	by	ADP
cana-1621	158	17	using	use	VERB
cana-1621	158	18	rank	rank	NOUN
cana-1621	158	19	aggregation	aggregation	NOUN
cana-1621	158	20	.	.	PUNCT
cana-1621	159	1	bangkok	bangkok	PROPN
cana-1621	159	2	,	,	PUNCT
cana-1621	159	3	thailand	thailand	PROPN
cana-1621	159	4	,	,	PUNCT
cana-1621	159	5	ieee	ieee	NOUN
cana-1621	159	6	[	[	X
cana-1621	159	7	7	7	NUM
cana-1621	159	8	]	]	X
cana-1621	159	9	shashi	shashi	PROPN
cana-1621	159	10	dahiya	dahiya	PROPN
cana-1621	159	11	,	,	PUNCT
cana-1621	159	12	s.	s.	PROPN
cana-1621	159	13	h.	h.	PROPN
cana-1621	159	14	,	,	PUNCT
cana-1621	159	15	.	.	PUNCT
cana-1621	160	1	s.	s.	PROPN
cana-1621	160	2	,	,	PUNCT
cana-1621	160	3	2016	2016	NUM
cana-1621	160	4	.	.	PUNCT
cana-1621	161	1	a	a	DET
cana-1621	161	2	rank	rank	NOUN
cana-1621	161	3	aggregation	aggregation	NOUN
cana-1621	161	4	algorithm	algorithm	NOUN
cana-1621	161	5	for	for	ADP
cana-1621	161	6	ensemble	ensemble	ADJ
cana-1621	161	7	of	of	ADP
cana-1621	161	8	multiple	multiple	ADJ
cana-1621	161	9	feature	feature	NOUN
cana-1621	161	10	selection	selection	NOUN
cana-1621	161	11	techniques	technique	NOUN
cana-1621	161	12	in	in	ADP
cana-1621	161	13	credit	credit	NOUN
cana-1621	161	14	risk	risk	NOUN
cana-1621	161	15	.	.	PUNCT
cana-1621	162	1	international	international	ADJ
cana-1621	162	2	journal	journal	NOUN
cana-1621	162	3	of	of	ADP
cana-1621	162	4	advanced	advanced	ADJ
cana-1621	162	5	research	research	NOUN
cana-1621	162	6	in	in	ADP
cana-1621	162	7	artificial	artificial	ADJ
cana-1621	162	8	intelligence	intelligence	NOUN
cana-1621	162	9	,	,	PUNCT
cana-1621	162	10	,	,	PUNCT
cana-1621	162	11	5(9	5(9	NUM
cana-1621	162	12	)	)	PUNCT
cana-1621	162	13	.	.	PUNCT
cana-1621	163	1	https://www.biorxiv.org/content/10.1101/2022.07.21.501057v1.full	https://www.biorxiv.org/content/10.1101/2022.07.21.501057v1.full	NOUN
cana-1621	163	2	communications	communication	NOUN
cana-1621	163	3	on	on	ADP
cana-1621	163	4	applied	apply	VERB
cana-1621	163	5	nonlinear	nonlinear	ADJ
cana-1621	163	6	analysis	analysis	NOUN
cana-1621	163	7	issn	issn	NOUN
cana-1621	163	8	:	:	PUNCT
cana-1621	163	9	1074	1074	NUM
cana-1621	163	10	-	-	PUNCT
cana-1621	163	11	133x	133x	NUM
cana-1621	163	12	vol	vol	NOUN
cana-1621	163	13	32	32	NUM
cana-1621	163	14	no	no	NOUN
cana-1621	163	15	.	.	NOUN
cana-1621	163	16	1	1	NUM
cana-1621	163	17	(	(	PUNCT
cana-1621	163	18	2025	2025	NUM
cana-1621	163	19	)	)	PUNCT
cana-1621	163	20	71	71	NUM
cana-1621	163	21	https://internationalpubls.com	https://internationalpubls.com	X
cana-1621	164	1	[	[	X
cana-1621	164	2	8	8	X
cana-1621	164	3	]	]	X
cana-1621	164	4	reem	reem	PROPN
cana-1621	164	5	salman	salman	PROPN
cana-1621	164	6	,	,	PUNCT
cana-1621	164	7	a.	a.	NOUN
cana-1621	164	8	a.	a.	PROPN
cana-1621	164	9	&	&	CCONJ
cana-1621	164	10	.	.	PUNCT
cana-1621	165	1	h.	h.	PROPN
cana-1621	165	2	s.	s.	PROPN
cana-1621	165	3	,	,	PUNCT
cana-1621	165	4	2022	2022	NUM
cana-1621	165	5	.	.	PUNCT
cana-1621	166	1	the	the	DET
cana-1621	166	2	stability	stability	NOUN
cana-1621	166	3	of	of	ADP
cana-1621	166	4	different	different	ADJ
cana-1621	166	5	aggregation	aggregation	NOUN
cana-1621	166	6	techniques	technique	NOUN
cana-1621	166	7	in	in	ADP
cana-1621	166	8	ensemble	ensemble	ADJ
cana-1621	166	9	feature	feature	NOUN
cana-1621	166	10	selection	selection	NOUN
cana-1621	166	11	.	.	PUNCT
cana-1621	167	1	journal	journal	PROPN
cana-1621	167	2	of	of	ADP
cana-1621	167	3	bigdata	bigdata	PROPN
cana-1621	167	4	,	,	PUNCT
cana-1621	167	5	9(51	9(51	NUM
cana-1621	167	6	)	)	PUNCT
cana-1621	167	7	.	.	PUNCT
cana-1621	168	1	[	[	X
cana-1621	168	2	9	9	NUM
cana-1621	168	3	]	]	SYM
cana-1621	168	4	apiletti	apiletti	PROPN
cana-1621	168	5	,	,	PUNCT
cana-1621	168	6	d.	d.	PROPN
cana-1621	168	7	,	,	PUNCT
cana-1621	168	8	baralis	baralis	PROPN
cana-1621	168	9	,	,	PUNCT
cana-1621	168	10	e.	e.	PROPN
cana-1621	168	11	,	,	PUNCT
cana-1621	168	12	cerquitelli	cerquitelli	PROPN
cana-1621	168	13	,	,	PUNCT
cana-1621	168	14	t.	t.	PROPN
cana-1621	168	15	,	,	PUNCT
cana-1621	168	16	garza	garza	PROPN
cana-1621	168	17	,	,	PUNCT
cana-1621	168	18	p.	p.	NOUN
cana-1621	168	19	,	,	PUNCT
cana-1621	168	20	pulvirenti	pulvirenti	PROPN
cana-1621	168	21	,	,	PUNCT
cana-1621	168	22	f.	f.	PROPN
cana-1621	168	23	,	,	PUNCT
cana-1621	168	24	&	&	CCONJ
cana-1621	168	25	venturini	venturini	PROPN
cana-1621	168	26	,	,	PUNCT
cana-1621	168	27	l.	l.	PROPN
cana-1621	168	28	(	(	PUNCT
cana-1621	168	29	2017	2017	NUM
cana-1621	168	30	)	)	PUNCT
cana-1621	168	31	.	.	PUNCT
cana-1621	169	1	frequent	frequent	ADJ
cana-1621	169	2	itemsets	itemset	NOUN
cana-1621	169	3	mining	mining	NOUN
cana-1621	169	4	for	for	ADP
cana-1621	169	5	big	big	ADJ
cana-1621	169	6	data	datum	NOUN
cana-1621	169	7	:	:	PUNCT
cana-1621	169	8	a	a	DET
cana-1621	169	9	comparative	comparative	ADJ
cana-1621	169	10	analysis	analysis	NOUN
cana-1621	169	11	.	.	PUNCT
cana-1621	170	1	big	big	ADJ
cana-1621	170	2	data	data	PROPN
cana-1621	170	3	research	research	NOUN
cana-1621	170	4	[	[	X
cana-1621	170	5	10	10	NUM
cana-1621	170	6	]	]	X
cana-1621	170	7	brownlee	brownlee	PROPN
cana-1621	170	8	,	,	PUNCT
cana-1621	170	9	j.	j.	PROPN
cana-1621	170	10	(	(	PUNCT
cana-1621	170	11	n.d	n.d	PROPN
cana-1621	170	12	.	.	PROPN
cana-1621	170	13	)	)	PUNCT
cana-1621	170	14	.	.	PUNCT
cana-1621	171	1	recursive	recursive	ADJ
cana-1621	171	2	feature	feature	NOUN
cana-1621	171	3	elimination	elimination	NOUN
cana-1621	171	4	(	(	PUNCT
cana-1621	171	5	rfe	rfe	NOUN
cana-1621	171	6	)	)	PUNCT
cana-1621	171	7	for	for	ADP
cana-1621	171	8	feature	feature	NOUN
cana-1621	171	9	selection	selection	NOUN
cana-1621	171	10	in	in	ADP
cana-1621	171	11	python	python	PROPN
cana-1621	171	12	.	.	PUNCT
cana-1621	172	1	retrieved	retrieve	VERB
cana-1621	172	2	from	from	ADP
cana-1621	172	3	machinelearningmastery	machinelearningmastery	NOUN
cana-1621	172	4	:	:	PUNCT
cana-1621	172	5	https://machinelearningmastery.com/rfe-feature-selection-in-python/	https://machinelearningmastery.com/rfe-feature-selection-in-python/	PROPN
cana-1621	173	1	[	[	X
cana-1621	173	2	11	11	NUM
cana-1621	173	3	]	]	X
cana-1621	173	4	d.	d.	PROPN
cana-1621	173	5	sculley	sculley	PROPN
cana-1621	173	6	,	,	PUNCT
cana-1621	173	7	rank	rank	NOUN
cana-1621	173	8	aggregation	aggregation	NOUN
cana-1621	173	9	for	for	ADP
cana-1621	173	10	similar	similar	ADJ
cana-1621	173	11	items	item	NOUN
cana-1621	173	12	,	,	PUNCT
cana-1621	173	13	department	department	NOUN
cana-1621	173	14	of	of	ADP
cana-1621	173	15	computer	computer	NOUN
cana-1621	173	16	science	science	PROPN
cana-1621	173	17	tufts	tufts	PROPN
cana-1621	173	18	university	university	PROPN
cana-1621	173	19	,	,	PUNCT
cana-1621	173	20	medford	medford	PROPN
cana-1621	173	21	,	,	PUNCT
cana-1621	173	22	ma	ma	PROPN
cana-1621	173	23	,	,	PUNCT
cana-1621	173	24	usa	usa	PROPN
cana-1621	173	25	dsculley@cs.tufts.edu	dsculley@cs.tufts.edu	PROPN
cana-1621	173	26	,	,	PUNCT
cana-1621	173	27	https://www.eecs.tufts.edu/~dsculley/papers/mergesimilarrank.pdf	https://www.eecs.tufts.edu/~dsculley/papers/mergesimilarrank.pdf	NOUN
cana-1621	173	28	[	[	X
cana-1621	173	29	12	12	NUM
cana-1621	173	30	]	]	X
cana-1621	173	31	devin	devin	PROPN
cana-1621	173	32	soni	soni	PROPN
cana-1621	173	33	,	,	PUNCT
cana-1621	173	34	introduction	introduction	NOUN
cana-1621	173	35	to	to	ADP
cana-1621	173	36	markov	markov	NOUN
cana-1621	173	37	chains	chain	NOUN
cana-1621	173	38	,	,	PUNCT
cana-1621	173	39	https://	https://	PROPN
cana-1621	173	40	towardsdatascience.com/	towardsdatascience.com/	NOUN
cana-1621	173	41	introduction	introduction	NOUN
cana-1621	173	42	-	-	PUNCT
cana-1621	173	43	to	to	ADP
cana-1621	173	44	-	-	PUNCT
cana-1621	173	45	markov	markov	NOUN
cana-1621	173	46	-	-	PUNCT
cana-1621	173	47	chains50da3645a50d	chains50da3645a50d	NOUN
cana-1621	173	48	[	[	X
cana-1621	173	49	13	13	NUM
cana-1621	173	50	]	]	X
cana-1621	173	51	brownlee	brownlee	PROPN
cana-1621	173	52	,	,	PUNCT
cana-1621	173	53	j.	j.	PROPN
cana-1621	173	54	,	,	PUNCT
cana-1621	173	55	2019	2019	NUM
cana-1621	173	56	.	.	PUNCT
cana-1621	174	1	https://machinelearningmastery.com/.	https://machinelearningmastery.com/.	ADJ
cana-1621	174	2	[	[	X
cana-1621	174	3	online	online	X
cana-1621	174	4	]	]	X
cana-1621	174	5	available	available	ADJ
cana-1621	174	6	at	at	ADP
cana-1621	174	7	:	:	PUNCT
cana-1621	174	8	https://machinelearningmastery.com/information-gain-and-mutual-information/	https://machinelearningmastery.com/information-gain-and-mutual-information/	PROPN
cana-1621	174	9	[	[	X
cana-1621	174	10	accessed	access	VERB
cana-1621	174	11	feruary	feruary	ADJ
cana-1621	174	12	2023	2023	NUM
cana-1621	174	13	]	]	PUNCT
cana-1621	174	14	.	.	PUNCT
cana-1621	175	1	[	[	X
cana-1621	175	2	14	14	NUM
cana-1621	175	3	]	]	X
cana-1621	175	4	lippman	lippman	PROPN
cana-1621	175	5	,	,	PUNCT
cana-1621	175	6	d.	d.	PROPN
cana-1621	175	7	,	,	PUNCT
cana-1621	175	8	n.d	n.d	PROPN
cana-1621	175	9	.	.	PROPN
cana-1621	175	10	votingtheory	votingtheory	PROPN
cana-1621	175	11	.	.	PUNCT
cana-1621	176	1	[	[	X
cana-1621	176	2	online	online	X
cana-1621	176	3	]	]	X
cana-1621	176	4	available	available	ADJ
cana-1621	176	5	at	at	ADP
cana-1621	176	6	:	:	PUNCT
cana-1621	176	7	http://www.opentextbookstore	http://www.opentextbookstore	PROPN
cana-1621	176	8	.	.	PUNCT
cana-1621	176	9	com	com	NOUN
cana-1621	176	10	/	/	SYM
cana-1621	176	11	mathinsociety	mathinsociety	NOUN
cana-1621	176	12	/	/	SYM
cana-1621	176	13	current/	current/	NOUN
cana-1621	176	14	votingtheory.pdf	votingtheory.pdf	X
cana-1621	176	15	[	[	X
cana-1621	176	16	accessed	access	VERB
cana-1621	176	17	2023	2023	NUM
cana-1621	176	18	]	]	PUNCT
cana-1621	176	19	.	.	PUNCT
cana-1621	177	1	[	[	X
cana-1621	177	2	15	15	NUM
cana-1621	177	3	]	]	PUNCT
cana-1621	177	4	anon	anon	NOUN
cana-1621	177	5	.	.	PROPN
cana-1621	177	6	,	,	PUNCT
cana-1621	177	7	2018	2018	NUM
cana-1621	177	8	.	.	PUNCT
cana-1621	178	1	devin	devin	PROPN
cana-1621	178	2	soni	soni	PROPN
cana-1621	178	3	.	.	PUNCT
cana-1621	179	1	[	[	X
cana-1621	179	2	online	online	X
cana-1621	179	3	]	]	X
cana-1621	179	4	available	available	ADJ
cana-1621	179	5	at	at	ADP
cana-1621	179	6	:	:	PUNCT
cana-1621	179	7	https://	https://	PROPN
cana-1621	179	8	towardsdatascience.com/	towardsdatascience.com/	NOUN
cana-1621	179	9	introduction	introduction	NOUN
cana-1621	179	10	-	-	PUNCT
cana-1621	179	11	to	to	ADP
cana-1621	179	12	-	-	PUNCT
cana-1621	179	13	markov	markov	NOUN
cana-1621	179	14	-	-	PUNCT
cana-1621	179	15	chains50da3645a50d	chains50da3645a50d	NOUN
cana-1621	179	16	[	[	X
cana-1621	179	17	accessed	access	VERB
cana-1621	179	18	2023	2023	NUM
cana-1621	179	19	]	]	PUNCT
cana-1621	179	20	.	.	PUNCT
cana-1621	180	1	[	[	X
cana-1621	180	2	16	16	NUM
cana-1621	180	3	]	]	PUNCT
cana-1621	180	4	anon	anon	PROPN
cana-1621	180	5	.	.	PROPN
cana-1621	180	6	,	,	PUNCT
cana-1621	180	7	n.d	n.d	PROPN
cana-1621	180	8	.	.	PROPN
cana-1621	180	9	borda	borda	PROPN
cana-1621	180	10	count	count	NOUN
cana-1621	180	11	.	.	PUNCT
cana-1621	181	1	[	[	X
cana-1621	181	2	online	online	X
cana-1621	181	3	]	]	X
cana-1621	181	4	available	available	ADJ
cana-1621	181	5	at	at	ADP
cana-1621	181	6	:	:	PUNCT
cana-1621	181	7	https://	https://	PROPN
cana-1621	181	8	en.wikipedia.org/	en.wikipedia.org/	PROPN
cana-1621	181	9	wiki	wiki	PROPN
cana-1621	181	10	/	/	SYM
cana-1621	181	11	borda_count	borda_count	PROPN
cana-1621	182	1	[	[	X
cana-1621	182	2	accessed	access	VERB
cana-1621	182	3	2023	2023	NUM
cana-1621	182	4	]	]	PUNCT
cana-1621	182	5	.	.	PUNCT
cana-1621	183	1	https://machinelearningmastery.com/rfe-feature-selection-in-python/	https://machinelearningmastery.com/rfe-feature-selection-in-python/	PROPN
cana-1621	183	2	mailto:dsculley@cs.tufts.edu	mailto:dsculley@cs.tufts.edu	PROPN
cana-1621	183	3	https://www.eecs.tufts.edu/~dsculley/papers/mergesimilarrank.pdf	https://www.eecs.tufts.edu/~dsculley/papers/mergesimilarrank.pdf	NOUN
cana-1621	183	4	https://machinelearningmastery.com/information-gain-and-mutual-information/	https://machinelearningmastery.com/information-gain-and-mutual-information/	ADV